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Polys NF, Polys N. @theSource: Welcome. IEEE COMPUTER GRAPHICS AND APPLICATIONS 2024; 44:69-73. [PMID: 38905024 PMCID: PMC11784925 DOI: 10.1109/mcg.2024.3384728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
This inaugural article sets the stage and scope for a new department in IEEE Computer Graphics and Applications: @theSource. In this department, we set out to address the questions, "How have open source projects and open Standards driven graphics innovations and applications?" and "What can we learn from them?" Thus, we are broadly concerned with how open communities and ecosystems have (and are) impacting computer graphics. The intent is to highlight: open source software (such as architectures, engines, frameworks, libraries, services); open Standards and open source data and models; and applications as well as the impacts of open graphics technologies. We also consider historical and summative reviews on the cultural and economic aspects of open source and open Standards graphics ecosystems, such as visualization and mixed reality.
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Hasanzadeh S, Polys NF, de la Garza JM. Presence, Mixed Reality, and Risk-Taking Behavior: A Study in Safety Interventions. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2020; 26:2115-2125. [PMID: 32070965 DOI: 10.1109/tvcg.2020.2973055] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Immersive environments have been successfully applied to a broad range of safety training in high-risk domains. However, very little research has used these systems to evaluate the risk-taking behavior of construction workers. In this study, we investigated the feasibility and usefulness of providing passive haptics in a mixed-reality environment to capture the risk-taking behavior of workers, identify at-risk workers, and propose injury-prevention interventions to counteract excessive risk-taking and risk-compensatory behavior. Within a mixed-reality environment in a CAVE-like display system, our subjects installed shingles on a (physical) sloped roof of a (virtual) two-story residential building on a morning in a suburban area. Through this controlled, within-subject experimental design, we exposed each subject to three experimental conditions by manipulating the level of safety intervention. Workers' subjective reports, physiological signals, psychophysical responses, and reactionary behaviors were then considered as promising measures of Presence. The results showed that our mixed-reality environment was a suitable platform for triggering behavioral changes under different experimental conditions and for evaluating the risk perception and risk-taking behavior of workers in a risk-free setting. These results demonstrated the value of immersive technology to investigate natural human factors.
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Skarbez R, Polys NF, Ogle JT, North C, Bowman DA. Immersive Analytics: Theory and Research Agenda. Front Robot AI 2019; 6:82. [PMID: 33501097 PMCID: PMC7805807 DOI: 10.3389/frobt.2019.00082] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 08/19/2019] [Indexed: 11/27/2022] Open
Abstract
Advances in a variety of computing fields, including “big data,” machine learning, visualization, and augmented/mixed/virtual reality, have combined to give rise to the emerging field of immersive analytics, which investigates how these new technologies support analysis and decision making. Thus far, we feel that immersive analytics research has been somewhat ad hoc, possibly owing to the fact that there is not yet an organizing framework for immersive analytics research. In this paper, we address this lack by proposing a definition for immersive analytics and identifying some general research areas and specific research questions that will be important for the development of this field. We also present three case studies that, while all being examples of what we would consider immersive analytics, present different challenges, and opportunities. These serve to demonstrate the breadth of immersive analytics and illustrate how the framework proposed in this paper applies to practical research.
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Tabor KM, Marquart GD, Hurt C, Smith TS, Geoca AK, Bhandiwad AA, Subedi A, Sinclair JL, Rose HM, Polys NF, Burgess HA. Brain-wide cellular resolution imaging of Cre transgenic zebrafish lines for functional circuit-mapping. eLife 2019; 8:42687. [PMID: 30735129 PMCID: PMC6392497 DOI: 10.7554/elife.42687] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 02/07/2019] [Indexed: 12/14/2022] Open
Abstract
Decoding the functional connectivity of the nervous system is facilitated by transgenic methods that express a genetically encoded reporter or effector in specific neurons; however, most transgenic lines show broad spatiotemporal and cell-type expression. Increased specificity can be achieved using intersectional genetic methods which restrict reporter expression to cells that co-express multiple drivers, such as Gal4 and Cre. To facilitate intersectional targeting in zebrafish, we have generated more than 50 new Cre lines, and co-registered brain expression images with the Zebrafish Brain Browser, a cellular resolution atlas of 264 transgenic lines. Lines labeling neurons of interest can be identified using a web-browser to perform a 3D spatial search (zbbrowser.com). This resource facilitates the design of intersectional genetic experiments and will advance a wide range of precision circuit-mapping studies.
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Marquart GD, Tabor KM, Horstick EJ, Brown M, Geoca AK, Polys NF, Nogare DD, Burgess HA. High-precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization. Gigascience 2018; 6:1-15. [PMID: 28873968 PMCID: PMC5597853 DOI: 10.1093/gigascience/gix056] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Accepted: 07/05/2017] [Indexed: 11/17/2022] Open
Abstract
Atlases provide a framework for spatially mapping information from diverse sources into a common reference space. Specifically, brain atlases allow annotation of gene expression, cell morphology, connectivity, and activity. In larval zebrafish, advances in genetics, imaging, and computational methods now allow the collection of such information brain-wide. However, due to technical considerations, disparate datasets may use different references and may not be aligned to the same coordinate space. Two recent larval zebrafish atlases exemplify this problem: Z-Brain, containing gene expression, neural activity, and neuroanatomical segmentations, was acquired using immunohistochemical stains, while the Zebrafish Brain Browser (ZBB) was constructed from live scans of fluorescent reporters in transgenic larvae. Although different references were used, the atlases included several common transgenic patterns that provide potential “bridges” for transforming each into the other's coordinate space. We tested multiple bridging channels and registration algorithms and found that the symmetric diffeomorphic normalization algorithm improved live brain registration precision while better preserving cell morphology than B-spline-based registrations. Symmetric diffeomorphic normalization also corrected for tissue distortion introduced during fixation. Multi-reference channel optimization provided a transformation that enabled Z-Brain and ZBB to be co-aligned with precision of approximately a single cell diameter and minimal perturbation of cell and tissue morphology. Finally, we developed software to visualize brain regions in 3 dimensions, including a virtual reality neuroanatomy explorer. This study demonstrates the feasibility of integrating whole brain datasets, despite disparate reference templates and acquisition protocols, when sufficient information is present for bridging. Increased accuracy and interoperability of zebrafish digital brain atlases will facilitate neurobiological studies.
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Xiao S, Muscente AD, Chen L, Zhou C, Schiffbauer JD, Wood AD, Polys NF, Yuan X. The Weng'an biota and the Ediacaran radiation of multicellular eukaryotes. Natl Sci Rev 2014. [DOI: 10.1093/nsr/nwu061] [Citation(s) in RCA: 97] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
The rise of multicellularity represents a major evolutionary transition and it occurred independently in multiple eukaryote clades. Although simple multicellular organisms may have evolved in the Mesoproterozoic Era or even earlier, complex multicellular eukaryotes began to diversify only in the Ediacaran Period, just before the Cambrian explosion. Thus, the Ediacaran fossil record can provide key paleontological evidence about the early radiation of multicellular eukaryotes that ultimately culminated in the Cambrian explosion. The Ediacaran Weng'an biota in South China hosts exceptionally preserved eukaryote fossils, including various acanthomorphic acritarchs, pseudoparenchymatous thalli, tubular microfossils, and spheroidal fossils such as Megasphaera, Helicoforamina, Spiralicellula, and Caveasphaera. Many of these fossils have been interpreted as multicellular eukaryotes, although alternative interpretations have also been proposed. In this review, we critically examine these various interpretations, focusing particularly on Megasphaera, which has been variously interpreted as a sulfur-oxidizing bacterium, a unicellular protist, a mesomycetozoean-like holozoan, a volvocine green alga, a stem-group animal, or a crown-group animal. We conclude that Megasphaera is a multicellular eukaryote with evidence for cell-to-cell adhesion, a flexible membrane unconstrained by a rigid cell wall, spatial cellular differentiation, germ–soma separation, and programmed cell death. These features are inconsistent with the bacterium, unicellular protist, and mesomycetozoean-like holozoan interpretations. Thus, the surviving hypotheses, particularly the stem-group animal and algal interpretations, should be further tested with additional evidence. The Weng'an biota also hosts cellularly differentiated pseudoparenchymatous thalli with specialized reproductive structures indicative of an affinity with florideophyte red algae. The other Weng'an fossils reviewed here may also be multicellular eukaryotes, although direct cellular evidence is lacking in some and phylogenetic affinities are poorly constrained in others. The Weng'an biota offers many research opportunities to resolve the life histories and phylogenetic diversity of early multicellular eukaryotes and to illuminate the evolutionary prelude to the Cambrian explosion.
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Hossain MS, Akbar M, Polys NF. Narratives in the network: interactive methods for mining cell signaling networks. J Comput Biol 2012; 19:1043-59. [PMID: 22897227 DOI: 10.1089/cmb.2011.0244] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In this article, we describe our work on graph mining as applied to the cellular signaling pathways in the Signal Transduction Knowledge Environment (STKE). We present new algorithms and a graphical tool that can help biologists discover relationships between pathways by looking at structural overlaps within the database. We address the problem of determining pathway relationships by using two data mining approaches: clustering and storytelling. In the first approach, our tool brings similar pathways to the same cluster, and in the second, our tool determines intermediate overlapping pathways that can lead biologists to new hypotheses and experiments regarding relationships between the pathways. We formulate the problem of discovering pathway relationships as a subgraph discovery problem and propose a new technique called Subgraph-Extension Generation (SEG), which outperforms the traditional Frequent Subgraph Discovery (FSG) approach by magnitudes. Our tool provides an interface to compare these two approaches with a variety of similarity measures and clustering techniques as well as in terms of computational performance measures such as runtime and memory consumption.
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Ullrich S, Kuhlen T, Polys NF, Evestedt D, Aratow M, John NW. Quantizing the void: extending Web3D for space-filling haptic meshes. Stud Health Technol Inform 2011; 163:670-676. [PMID: 21335877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
In this paper we summarize the progress of the Web3D scene graph model, and associated standards, specifically Extensible 3D (X3D) in the domain of medical simulation. Historically, the Web3D nodesets have focused on the representation and rendering of point, line or surface geometry. More recently, significant progress in X3D Volume rendering has been made available through the co-operative DICOM work item, n-Dimensional Presentation States. However, here we outline the need for a standard for simulation meshes and review several related approaches. As a result, we propose preliminary requirements for a simulation mesh standard and provide several use case scenarios of how Web3D and haptic technologies can aid the fulfillment of these requirements. We conclude with an X3D proposal to describe simulation meshes for soft (deformable) bodies.
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Polys NF, Brutzman D, Steed A, Behr J. Future standards for immersive VR: report on the IEEE Virtual Reality 2007 workshop. IEEE COMPUTER GRAPHICS AND APPLICATIONS 2008; 28:94-99. [PMID: 18350937 DOI: 10.1109/mcg.2008.29] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
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Shapiro M, Duca KA, Lee K, Delgado-Eckert E, Hawkins J, Jarrah AS, Laubenbacher R, Polys NF, Hadinoto V, Thorley-Lawson DA. A virtual look at Epstein-Barr virus infection: simulation mechanism. J Theor Biol 2008; 252:633-48. [PMID: 18371986 DOI: 10.1016/j.jtbi.2008.01.032] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2007] [Revised: 01/09/2008] [Accepted: 01/28/2008] [Indexed: 10/22/2022]
Abstract
Epstein-Barr virus (EBV) is an important human pathogen that establishes a life-long persistent infection and for which no precise animal model exists. In this paper, we describe in detail an agent-based model and computer simulation of EBV infection. Agents representing EBV and sets of B and T lymphocytes move and interact on a three-dimensional grid approximating Waldeyer's ring, together with abstract compartments for lymph and blood. The simulation allows us to explore the development and resolution of virtual infections in a manner not possible in actual human experiments. Specifically, we identify parameters capable of inducing clearance, persistent infection, or death.
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Duca KA, Shapiro M, Delgado-Eckert E, Hadinoto V, Jarrah AS, Laubenbacher R, Lee K, Luzuriaga K, Polys NF, Thorley-Lawson DA. A virtual look at Epstein-Barr virus infection: biological interpretations. PLoS Pathog 2007; 3:1388-400. [PMID: 17953479 PMCID: PMC2034398 DOI: 10.1371/journal.ppat.0030137] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2006] [Accepted: 07/30/2007] [Indexed: 11/19/2022] Open
Abstract
The possibility of using computer simulation and mathematical modeling to gain insight into biological and other complex systems is receiving increased attention. However, it is as yet unclear to what extent these techniques will provide useful biological insights or even what the best approach is. Epstein–Barr virus (EBV) provides a good candidate to address these issues. It persistently infects most humans and is associated with several important diseases. In addition, a detailed biological model has been developed that provides an intricate understanding of EBV infection in the naturally infected human host and accounts for most of the virus' diverse and peculiar properties. We have developed an agent-based computer model/simulation (PathSim, Pathogen Simulation) of this biological model. The simulation is performed on a virtual grid that represents the anatomy of the tonsils of the nasopharyngeal cavity (Waldeyer ring) and the peripheral circulation—the sites of EBV infection and persistence. The simulation is presented via a user friendly visual interface and reproduces quantitative and qualitative aspects of acute and persistent EBV infection. The simulation also had predictive power in validation experiments involving certain aspects of viral infection dynamics. Moreover, it allows us to identify switch points in the infection process that direct the disease course towards the end points of persistence, clearance, or death. Lastly, we were able to identify parameter sets that reproduced aspects of EBV-associated diseases. These investigations indicate that such simulations, combined with laboratory and clinical studies and animal models, will provide a powerful approach to investigating and controlling EBV infection, including the design of targeted anti-viral therapies. The possibility of using computer simulation and mathematical modeling to gain insight into biological systems is receiving increased attention. However, it is as yet unclear to what extent these techniques will provide useful biological insights or even what the best approach is. Epstein–Barr virus (EBV) provides a good candidate to address these issues. It persistently infects most humans and is associated with several important diseases, including cancer. We have developed an agent-based computer model/simulation (PathSim, Pathogen Simulation) of EBV infection. The simulation is performed on a virtual grid that represents the anatomy where EBV infects and persists. The simulation is presented on a computer screen in a form that resembles a computer game. This makes it readily accessible to investigators who are not well versed in computer technology. The simulation allows us to identify switch points in the infection process that direct the disease course towards the end points of persistence, clearance, or death, and identify conditions that reproduce aspects of EBV-associated diseases. Such simulations, combined with laboratory and clinical studies and animal models, provide a powerful approach to investigating and controlling EBV infection, including the design of targeted anti-viral therapies.
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