@theSource: Welcome.

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.

Making Cardiopulmonary Exercise Testing Interpretable for Clinicians.

ABSTRACT: Cardiopulmonary exercise testing (CPET) is a dynamic clinical tool for determining the cause for a person's exercise limitation. CPET provides clinicians with fundamental knowledge of the coupling of external to internal respiration (oxygen and carbon dioxide) during exercise. Subtle perturbations in CPET parameters can differentiate exercise responses among individual patients and disease states. However, perhaps because of the challenges in interpretation given the amount and complexity of data obtained, CPET is underused. In this article, we review fundamental concepts in CPET data interpretation and visualization. We also discuss future directions for how to best use CPET results to guide clinical care. Finally, we share a novel three-dimensional graphical platform for CPET data that simplifies conceptualization of organ system-specific (cardiac, pulmonary, and skeletal muscle) exercise limitations. Our goal is to make CPET testing more accessible to the general medical provider and make the test of greater use in the medical toolbox.

Presence, Mixed Reality, and Risk-Taking Behavior: A Study in Safety Interventions.

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.

Development of a Responsible Policy Index to Improve Statutory and Self-Regulatory Policies that Protect Children's Diet and Health in the America's Region.

In 2010, 193 Member States of the World Health Organization (WHO) endorsed World Health Assembly Resolution WHA63.14 to restrict the marketing of food and beverage products high in fat, sugar and salt (HFSS) to children to prevent obesity and non-communicable diseases (NCDs). No study has examined HFSS marketing policies across the WHO regional office countries in the Americas. Between 2018 and 2019, a transdisciplinary team examined policies to restrict HFSS food and beverage product marketing to children to develop a responsible policy index (RESPI) that provides a quality score based on policy characteristics and marketing techniques. After designing the RESPI, we conducted a comprehensive literature review through October 2019 to examine policies in 14 countries in the WHO Americans Region. We categorized policies (n = 38) as either self-regulatory or statutory and calculated the RESPI scores, ranked from 0 (lowest) to 10 (highest). Results showed Brazil, Canada, Chile, and Uruguay had the highest RESPI scores associated with statutory policies that restricted point of sale, cartoon, licensed media characters and celebrities; and HFSS products in schools and child care settings, and broadcast and print media. Policymakers can use the RESPI tool to evaluate marketing policies within and across geopolitical boundaries to protect children's diet and health.

Mapping the Celebrity Endorsement of Branded Food and Beverage Products and Marketing Campaigns in the United States, 1990-2017.

Celebrity endorsement used to promote energy-dense and nutrient-poor (EDNP) food and beverage products may contribute to poor dietary habits. This study examined celebrity endorsement of branded food and beverage products and marketing campaigns in the United States (US) from 1990 to 2017. Celebrity endorsement data were collected from peer-reviewed and grey literature. Interactive data visualizations were created for the endorsement relationships between celebrities, companies and products whose nutritional profiles were compared with the US Department of Agriculture's (USDA's) Smart Snacks Standards. Logistic regression was used to explore associations between celebrities' demographic profiles and the nutritional profiles of products. Results showed 542 celebrities were associated with 732 endorsements representing 120 brands of 59 companies across 10 food and beverage categories. Two thirds (67.2%; n = 80) of the brands represented EDNP products that did not align with the USDA's Smart Snacks Standards. Logistic regression analysis indicated that Millennial (p = 0.008) and male celebrities (p = 0.041) were more likely to endorse EDNP products than Generation Z teen and female celebrities, respectively. No statistical significance was observed for celebrities of other demographic profiles. This study may inform future policies and actions of the US government, industry, researchers and consumer advocacy organizations to use celebrity endorsement to promote healthy food environments for Americans.

Brain-wide cellular resolution imaging of Cre transgenic zebrafish lines for functional circuit-mapping.

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.

Immersive Analytics: Theory and Research Agenda.

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.

High-precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization.

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.

Narratives in the network: interactive methods for mining cell signaling networks.

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.

Quantizing the void: extending Web3D for space-filling haptic meshes.

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.

A virtual look at Epstein-Barr virus infection: biological interpretations.

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.