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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

EVALUATION OF EXISTING PUBLIC DOSE LIMITS APPLIED TO RECREATIONAL SPACEFLIGHT

Abstract Establishing realistic radiation dose limits with a solid scientific basis is a key component of the ‘as low as reasonably achievable’ (ALARA) principle. Although existing occupational dose limits have been established for civil astronauts, with the rise in popularity and technological maturation of the ‘space tourism’ sector, there does not appear to be considerable discussion on the subject of non-occupational astronaut dose limits. The necessity to come to a collective decision on dose limits and radiation safety procedures for recreational spaceflight is urgent and imperative to maintain ALARA goals, as existing federal dose limits to the public cannot be adequately or universally applied to the space tourism sector. Development of an entirely new set of regulations and guidelines should also provide long-term benefits in public perception as evidence of safety commitments from decision makers and the community in protecting passengers from radiological risks balanced with other spaceflight hazards.

Long, Michael A. (ORCID:0000000181363476)↗
DOE OSTI2024

Forecasting fluid-injection induced seismicity to choose the best injection strategy for safety and efficiency

Induced seismicity poses a challenge to the development of Enhanced Geothermal Systems (EGS). Improving monitoring and forecasting techniques is essential to mitigate induced seismicity and thereby fostering a positive perception of EGS projects among local authorities and population. Induced seismicity is the result of complex and coupled thermo-hydro-mechanical-chemical mechanisms. Injection flux and pressure are crucial controlling parameters for both hydraulic stimulation and circulation protocols. We develop a methodology combining a hydro-mechanical model with a seismicity rate model to estimate the magnitude and frequency of mainshocks and aftershocks induced by fluid injection. We apply the methodology to the case of the Basel EGS (2006, Switzerland) to compare the effects of progressive, cyclic and constant injections on the mechanical response of discrete faults. Results from the coupled hydro-mechanical models show that the pore pressure diffusion and consequent enhancement of fault permeability are limited to the vicinity of the injection well during cyclic injection. Additionally, constant injection induces seismicity from the start of the injection but enhances the permeability of most of the faults within a shorter duration, inducing less post-injection seismicity. The methodology can be adapted to any numerical model and allows new projects to be developed by anticipating the safest injection protocol. This article is part of the theme issue ‘Induced seismicity in coupled subsurface systems’.

58 GEOSCIENCES↗
DOE OSTI2021

The Enterprise , a massive transposon carrying Spok meiotic drive genes

The genomes of eukaryotes are full of parasitic sequences known as transposable elements (TEs). Here, we report the discovery of a putative giant tyrosine-recombinase-mobilized DNA transposon, Enterprise, from the model fungus Podospora anserina. Previously, we described a large genomic feature called the Spok block which is notable due to the presence of meiotic drive genes of the Spok gene family. The Spok block ranges from 110 kb to 247 kb and can be present in at least four different genomic locations within P. anserina, despite what is an otherwise highly conserved genome structure. We propose that the reason for its varying positions is that the Spok block is not only capable of meiotic drive but is also capable of transposition. More precisely, the Spok block represents a unique case where the Enterprise has captured the Spoks, thereby parasitizing a resident genomic parasite to become a genomic hyperparasite. Furthermore, we demonstrate that Enterprise (without the Spoks) is found in other fungal lineages, where it can be as large as 70 kb. Lastly, we provide experimental evidence that the Spok block is deleterious, with detrimental effects on spore production in strains which carry it. This union of meiotic drivers and a transposon has created a selfish element of impressive size in Podospora, challenging our perception of how TEs influence genome evolution and broadening the horizons in terms of what the upper limit of transposition may be.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Revealing the Emergence of Classicality Using Nitrogen-Vacancy Centers

The origin of classical reality in our quantum world is a long-standing mystery. Here, we examine a nitrogen-vacancy center in diamond evolving in the presence of its magnetic nuclear spin environment which is formed by the natural appearance of carbon 13 C atoms in the diamond lattice, to study quantum Darwinism—the proliferation of information about preferred quantum states throughout the world via the environment. This redundantly imprinted information accounts for the perception of objective reality, as it is independently accessible by many without perturbing the system of interest. To observe this process, we implement a novel dynamical decoupling scheme that enables the measurement and control of several nuclear spins (the environment $\mathcal{E}$) interacting with a nitrogen vacancy (the system $\mathcal{S}$). Our experiment demonstrates that, in the course of the decoherence of $\mathcal{S}$, redundant information is indeed imprinted onto $\mathcal{E}$, giving rise to incipient classical objectivity—a consensus recorded in redundant copies, and available from the fragments of the nuclear spin environment E, about the state of $\mathcal{S}$. This provides the first laboratory verification of the process responsible for the emergence of the objective classical world from the underlying quantum substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Investigating Users’ Privacy Concerns of Internet of Things (IoT) Smart Devices

Although the number of smart Internet of Things (IoT) devices has grown in recent years, the public's perception of how effectively these devices secure IoT data has been questioned. Many IoT users do not have a good level of confidence in the security or privacy procedures implemented within IoT smart devices for protecting personal IoT data. Moreover, determining the level of confidence end users have in their smart devices is becoming a major challenge. In this paper, we present a study that focuses on identifying privacy concerns IoT end users have when using IoT smart devices. We investigated multiple smart devices and conducted a survey to identify users’ privacy concerns. Furthermore, we identify five IoT privacy-preserving (IoTPP) control policies that we define and employ in comparing the privacy measures implemented by various popular smart devices. Results from our study show that the over 86% of participants are very or extremely concerned about the security and privacy of their personal data when using smart IoT devices such as Google Nest Hub or Amazon Alexa. In addition, our study shows that a significant number of IoT users may not be aware that their personal data is collected, stored or shared by IoT devices.

Joy, Daniel↗
DOE OSTI2023

How R Developers explain their Package Choice: A Survey

Background: Contemporary software development relies heavily on reusing already implemented functionality, usually in the form of packages. Aims: We aim to shed light on developers' preferences when selecting packages in R language. Method: To do that, we create and administer a survey to over 1000 developers who have added one of two common dataframe enhancement libraries in R to their projects: data.table or tidyr. We design a questionnaire using the Social Contagion Theory (SCT) following prior work on technology adoption and ensure that key dimensions affecting developer choice are considered. Results: Of the 1085 developers we contacted, 803 completed the survey asking them to prioritize various factors known to affect developer perceptions of package quality and to provide their background. Most developers self-identified as data scientists with two to five years of work experience. We found significant differences between the preferences of developers who chose data.table and tidyr. Surprisingly, package reputation based on easy-to-see measures, such as the number of stars on GitHub, was not an important factor for either group. Conclusions: Our findings demonstrate the inherently social nature of package adoption. They can help design future studies on how different populations of developers make decisions on which software packages to use in their projects. Finally, package developers and maintainers can benefit by better understanding the prime concerns of the users of their packages.

Malviya Thakur, Addi↗
DOE OSTI2021

Haze Mitigation in High-Resolution Satellite Imagery using Enhanced Style-Transfer Neural Network and Normalization Across Multiple GPUs

Despite recent advances in deep learning approaches, haze mitigation in large satellite images is still a challenging problem. Due to amorphous nature of haze, object detection or image segmentation approaches are not applicable. Also it is practically infeasible to obtain ground truths for training. Bounded memory capacity of GPUs is another constraint that limits the size of image to be processed. In this paper, we propose a style transfer based neural network approach to mitigate haze in a large overhead imagery. The network is trained without paired ground truths; further, perception loss is added to restore vivid colors, enhance contrast and minimize artifacts. The paper also illustrates our use of multiple GPUs in a collective way to produce a single coherent clear image where each GPU dehazes different portions of a large hazy image.

Park, Byung↗
DOE OSTI2020

Attack on Grid Event Cause Analysis: An Adversarial Machine Learning Approach

With the ever-increasing reliance on data for data-driven applications in power grids, such as event cause analysis, the authenticity of data streams has become crucially important. The data can be prone to adversarial stealthy attacks aiming to manipulate the data such that residual-based bad data detectors cannot detect them, and the perception of system operators or event classifiers changes about the actual event. This paper investigates the impact of adversarial attacks on convolutional neural network-based event cause analysis frameworks. We have successfully verified the ability of adversaries to maliciously misclassify events through stealthy data manipulations. The vulnerability assessment is studied with respect to the number of compromised measurements. Furthermore, a defense mechanism to robustify the performance of the event cause analysis is proposed. The effectiveness of adversarial attacks on changing the output of the framework is studied using the data generated by real-time digital simulator (RTDS) under different scenarios such as type of attacks and level of access to data.

Niazazari, Iman↗
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2023

Numerical and Visual Representations of Uncertainty Lead to Different Patterns of Decision Making

Although visualizations are a useful tool for helping people to understand information, they can also have unintended effects on human cognition. This is especially true for uncertain information, which is difficult for people to understand. Prior work has found that different methods of visualizing uncertain information can produce different patterns of decision making from users. However, uncertainty can also be represented via text or numerical information, and few studies have systematically compared these types of representations to visualizations of uncertainty. We present two experiments that compared visual representations of risk (icon arrays) to numerical representations (natural frequencies) in a wildfire evacuation task. Like prior studies, we found that different types of visual cues led to different patterns of decision making. In addition, our comparison of visual and numerical representations of risk found that people were more likely to evacuate when they saw visualizations than when they saw numerical representations. These experiments reinforce the idea that design choices are not neutral: seemingly minor differences in how information is represented can have important impacts on human risk perception and decision making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

VISILIENCE: An Interactive Visualization Framework for Resilience Analysis using Control-Flow Graph

Soft errors have become one of the major concerns for the error resilience of HPC applications, as those errors can cause HPC applications to generate serious outcomes such as Silent Data Corruptions (SDCs). A large body of approaches has been proposed to analyze the resilience of HPC applications. However, existing studies rarely address the challenges of the analysis result perception. Specifically, resilience analysis techniques often produce a massive volume of unstructured data, making it difficult for programmers to conduct the resilience analysis due to non-intuitive raw data. Furthermore, different analysis models produce diverse results with multiple levels of details, which may create hurdles to compare and explore the resilience of HPC program execution. To this end, we present VISILIENCE, an interactive VISual resILIENCE analysis framework to allow programmers to facilitate the resilience analysis of HPC applications. In particular, VISILIENCE leverages an effective visualization approach Control Flow Graph (CFG) to present a function execution. In addition, three widely-used models for resilience analysis (i.e., Y-Branch, IPAS, and TRIDENT) are seamlessly embedded into the framework for resilience analysis and result comparison. Multiple case studies have been conducted to demonstrate the effectiveness of our proposed framework VISILIENCE.

Jiang, Hailong↗
DOE OSTI2022

Making Invisible Visible: Data-Driven Seismic Inversion With Spatio-Temporally Constrained Data Augmentation

Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of obtaining data through expensive physical experiments, instruments, and simulations, data augmentation techniques for scientific applications have emerged as a new direction for obtaining scientific data recently. However, existing data augmentation techniques originating from computer vision yield physically unacceptable data samples that are not helpful for the domain problems that we are interested in. In this article, we develop new data augmentation techniques based on convolutional neural networks. Specifically, our generative models leverage different physics knowledge (such as governing equations, observable perception, and physics phenomena) to improve the quality of the synthetic data. To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO 2 leakage data. Our interest is to invert for subsurface velocity models associated with very small CO 2 leakage. We validate the performance of our methods using comprehensive numerical tests. Here via comparison and analysis, we show that data-driven seismic imaging can be significantly enhanced by using our data augmentation techniques. Particularly, the imaging quality has been improved by 15% in test scenarios of general-sized leakage and 17% in small-sized leakage when using an augmented training set obtained with our techniques.

58 GEOSCIENCES↗
DOE OSTI2021

Real-Time Omnidirectional Stereo Rendering: Generating 360° Surround-View Panoramic Images for Comfortable Immersive Viewing

Surround-view panoramic images and videos have become a popular form of media for interactive viewing on mobile devices and virtual reality headsets. Viewing such media provides a sense of immersion by allowing users to control their view direction and experience an entire environment. When using a virtual reality headset, the level of immersion can be improved by leveraging stereoscopic capabilities. Stereoscopic images are generated in pairs, one for the left eye and one for the right eye, and result in providing an important depth cue for the human visual system. For computer generated imagery, rendering proper stereo pairs is well known for a fixed view. However, it is much more difficult to create omnidirectional stereo pairs for a surround-view projection that work well when looking in any direction. One major drawback of traditional omnidirectional stereo images is that they suffer from binocular misalignment in the peripheral vision as a user's view direction approaches the zenith / nadir (north / south pole) of the projection sphere. This paper presents a real-time geometry-based approach for omnidirectional stereo rendering that fits into the standard rendering pipeline. Our approach includes tunable parameters that enable pole merging - a reduction in the stereo effect near the poles that can minimize binocular misalignment. Results from a user study indicate that pole merging reduces visual fatigue and discomfort associated with binocular misalignment without inhibiting depth perception.

360° panorama↗
DOE OSTI2021

K in an Urban World: New Contexts for Hydraulic Conductivity

Abstract Hydraulic conductivity ( K ) is a key hydrologic parameter widely recognized to be difficult to estimate and constrain, with little consistent assessment in disturbed, urbanized soils. To estimate K , it is either measured, or simulated by pedotransfer functions, which relate K to easily measured soil properties. We measured K in urbanized soils by double‐ring infiltrometer ( K dring ), near‐saturated tension infiltrometry ( K minidisk ), and constant head borehole permeametry ( K borehole ), along with other soil properties across the major soil orders in 12 United States cities. We compared measured K with that predicted from the pedotransfer function, ROSETTA. We found that regardless of soil texture, K dring was consistently larger than K minidisk ; with the latter having slightly less sample variance. K borehole was dependent upon specific subsurface conditions, and contrary to common expectations, did not always decrease with depth. Based on either soil textural class, or percent textural separates (sand, silt clay), ROSETTA did not accurately predict measured K for surface nor subsurface soils. We go on to discuss how K varies in urban landscapes, the role of measurement methods and artifacts in the perception of this metric, and implications for hydrologic modeling. Overall, we aim to inspire consistency and coherence when addressing K ‐related challenges in sustainable urban water management.

Shuster, W. D.↗
DOE OSTI2023

Neurobehavioral symptoms in children born extremely preterm: A Swedish National Study

Abstract Aim To determine the prevalence of neurobehavioral symptoms at 6.5 years in children born extremely preterm (EPT, <27 weeks' gestation). Methods Population‐based cohort study of infants born EPT in Sweden from 2004 to 2007. Of 486 survivors 375 were assessed and compared with 369 matched term‐born controls. EPT children free from neurosensory and intellectual disabilities (neurodevelopmental disabilities [NDD]‐free, n = 236) were compared separately. Standardised questionnaires were used to assess parental ratings of hyperactivity and attention, emotional, peer‐relation, conduct and social problems; and deficits in perception, language and memory. Results EPT children had more reported problems in all assessed neurobehavioral domains than controls, with more than three times greater odds for most outcomes. Except for conduct problems, increased problems were identified also in NDD–free children. The odds of having neurobehavioral problems in ≥3 co‐occurring domains were five (whole EPT group) and three (NDD‐free group) times higher than in controls. Conclusion EPT children with or without NDD have more neurobehavioral problems in multiple domains than term peers. Ongoing assessments of behaviour until school age or beyond should recognise early symptoms of attention, everyday social problems, perceptual, emotional or language difficulties.

Serenius, Fredrik↗
DOE OSTI2024

The Connected We St@nd programme: A feasibility pilot study of an online self‐management intervention for adults on in‐centre haemodialysis and family caregivers

Abstract Objective The ‘Connected We St@nd’ is an online self‐management intervention programme for people receiving in‐centre haemodialysis and family caregivers that combines an educational and psychosocial support component. This study aimed to evaluate its feasibility and acceptability before proceeding to a large‐scale trial. Design This was a pre‐post single‐arm feasibility pilot study conducted with adults undergoing in‐centre haemodialysis and family caregivers. Methods Feasibility was based on eligibility, consent, retention, completion and intervention adherence rates, while acceptability was assessed in post‐intervention focus group interviews. Results Twenty‐six people (16 adults on haemodialysis and 10 family caregivers) recruited through social networks completed the intervention. Consent, retention and completion rates were excellent (>90%) and eligibility (77.5%) and intervention adherence were satisfactory (69% for the psychosocial support sessions). Qualitative findings revealed that participants shared positive feelings regarding their participation in the programme. The valuable interactions with group peers and health psychologists during the support sessions, the perception of the adequacy and coherence of the programme's contents and materials and the participants' confidence in using the platform developed to deliver the intervention were some of the aspects highlighted as facilitators of intervention acceptability. Additionally, people on haemodialysis and caregivers reported that participation in the programme brought several educational and emotional benefits (e.g., additional disease‐related knowledge, improved communication and coping skills, greater confidence in managing dialysis complications or caregiving demands) that helped increase their self‐management skills and psychosocial adjustment to the demands of kidney failure and renal therapies. Conclusions The results suggested that the ‘Connected We St@nd’ programme is likely to be feasible and acceptable for adults on haemodialysis and family caregivers, thus representing a promising resource for the future of interdisciplinary renal rehabilitation. Suggestions were made to fine‐tune the intervention design to proceed with a large‐scale trial.

Sousa, Helena↗
DOE OSTI2018

Evidence for lack of direct causality between pain and affective disturbances in a rat peripheral neuropathy model

Chronic pain is frequently accompanied by the manifestation of emotional disturbances and cognitive deficits. While a causality relation between pain and emotional/cognitive disturbances is generally assumed, several observations suggest a temporal dissociation and independent mechanisms. We therefore studied Sprague‐Dawley rats that presented a natural resistance to pain manifestation in a neuropathy model (spared nerve injury [SNI]) and compared their performance in a battery of behavioral paradigms—anxiety, depression and fear memory—with animals that presented a pain phenotype. Afterward, we performed an extensive volumetric analysis across prefrontal, orbitofrontal and insular cortical areas. The majority of SNI animals manifested mechanical allodynia (low threshold [LT]), but 13% were similar to Sham controls (high threshold [HT]). Readouts of spontaneous hypersensivity (paw flinches) were also significantly reduced in HT and correlated with allodynia. To increase the specificity of our findings, we segregated the SNI animals in those with left (SNI‐L) and right (SNI‐R) lesions and the lack of association between pain and behavior still remains. Left‐lesioned animals, independent of the LT or HT phenotype, presented increased anxiety‐like behaviors and decreased well‐being. In contrast, we found that the insular cortex (agranular division) was significantly smaller in HT than in LT. To conclude, pain and emotional disturbances observed following nerve injury are to some extent segregated phenomena. Also, HT and LT SNI presented differences in insular volumes, an area vastly implicated in pain perception, suggesting a supraspinal involvement in the manifestation of these phenotypes.

Guimarães, Marco R.↗