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At least 577 records · Page 32

Spatial Mapping of Riverbed Grain-Size Distribution Using Machine Learning

Recent alluvial sediments in riverbeds play a significant role in controlling hydrologic exchange flows (HEFs) in river systems. The alluvial layer is usually associated with strong heterogeneity in physical properties (e.g., permeability and hydraulic conductivity), which affects local HEFs and therefore biogeochemical processes. The spatial distribution of these physical properties needs to be determined to inform the numerical models used to reveal the realistic hydro-biogeochemical behaviors. Such information can be obtained based on the intrinsic link between sediment grain-size distribution and hydraulic properties where sediment texture information is available. However, grain-size measurements are usually spatially sparse and do not have adequate coverage and resolution, particularly for a relatively large domain such as the Hanford Reach of the Columbia River. In this paper, we adopted machine learning (ML) approaches for categorizing and mapping the spatial distributions of riverbed substrate grain size and filling in missing areas of substrate data using the ML models along the reach. Such ML models for substrate size mapping were trained at 13,372 locations using measured substrate sizes along with observed and simulated attributes, including bathymetric attributes (e.g., elevation, slope, and aspect ratio) from LIDAR and bathymetric surveys, and hydrodynamic properties (e.g., water depth, velocity, shear stress, and their statistical moments). An ensemble bagging-based ML technique, Random Forest, was adopted to identify the most influential factors as predictors to develop the predictive models with over-fitting issues addressed. The models were evaluated with respect to each individual substrate size class and the lumped group, and then used to generate the final substrate size maps covering all the grid cells in the numerical modeling domain.

54 ENVIRONMENTAL SCIENCES↗

Improving Land Cover Product-Based Estimates of the Extent of Fragmented Cover Types

The effects of changing land use/land cover on regional and global climate ecosystems depends on accurate estimates of the extent of critical land cover types such as Arctic wetlands and fire scars in boreal forests. To address this information requirement, land cover products at coarse spatial resolution such as Advanced Very High Resolution Radiometer (AVHRR) -based maps and the MODIS Land Cover Product are being produced. The accuracy of the extent of highly fragmented cover types such as fire scars and ponds is in doubt because much (the numerous scars and ponds smaller than the pixel size) is missed. A promising method for improving areal estimates involves modeling the observed distribution of the fragment sizes as a type of truncated distribution, then estimating the sum of unobserved sizes in the lower, truncated tail and adding it to the sum of observed fragment sizes. The method has been tested with both simulated and actual cover products.

Hlavka, Christine A.↗

Mississippi Company Using NASA Software Program to Provide Unique Imaging Service: DATASTAR Success Story

DATASTAR, Inc., of Picayune, Miss., has taken NASA's award-winning Earth Resources Laboratory Applications (ELAS) software program and evolved it to the point that the company is now providing a unique, spatial imagery service over the Internet. ELAS was developed in the early 80's to process satellite and airborne sensor imagery data of the Earth's surface into readable and useable information. While there are several software packages on the market that allow the manipulation of spatial data into useable products, this is usually a laborious task. The new program, called the DATASTAR Image Processing Exploitation, or DIPX, Delivery Service, is a subscription service available over the Internet that takes the work out of the equation and provides normalized geo-spatial data in the form of decision products.

Source record↗

Conflict resolution maneuvers during near miss encounters with cockpit traffic displays

The benefits and liabilities associated with pilots' use of a cockpit traffic display to assess the threat posed by air traffic and to make small maneuvers to avoid situations which would result in collision avoidance advisories are experimentally studied. The crew's task was to fly a simulated wide-body aircraft along a straight course at constant altitude while intruder aircraft appeared on a variety of converging trajectories. The main experimental variables were the amount and quality of the information displayed on the intruder aircraft's estimated future position. Pilots were to maintain a horizontal separation of at least 1.5 nautical miles or a vertical separation of 500 ft, so that collision avoidance advisories would not be triggered. The results show that pilots could usually maneuver to provide the specified separation but often made course deviations greater than 1.5 nm or 500 ft.

Palmer, E.↗

UAS Air Traffic Controller Acceptability Study-2: Effects of Communications Delays and Winds in Simulation

This study evaluated the effects of Communications Delays and Winds on Air Traffic Controller ratings of acceptability of horizontal miss distances (HMDs) for encounters between UAS and manned aircraft in a simulation of the Dallas-Ft. Worth East-side airspace. Fourteen encounters per hour were staged in the presence of moderate background traffic. Seven recently retired controllers with experience at DFW served as subjects. Guidance provided to the UAS pilots for maintaining a given HMD was provided by information from self-separation algorithms displayed on the Multi-Aircraft Simulation System. Winds tested did not affect the acceptability ratings. Communications delays tested included 0, 400, 1200, and 1800 msec. For longer communications delays, there were changes in strategy and communications flow that were observed and reported by the controllers. The aim of this work is to provide useful information for guiding future rules and regulations applicable to flying UAS in the NAS.

Comstock, James R., Jr.↗

Moving Away from Ones and Zeros, Designing a Ground Data System Based on Higher Levels of Abstraction

Previous JPL ground systems have been designed with the Ground Data System (GDS) engineer in mind. The focus on these systems has been on packaging and delivery of low level information (frames, packets, telemetry values) to the end user. It was not that long ago when project teams would be huddled over a workstation, examining crude displays of telemetry bits organized in various ways, trying to determine the status of a spacecraft. Understanding the data often required additional levels of GDS expertise, or worse, transformation of the raw data into alternative formats followed by ingestion into other tools so that the data became meaningful. The primary focus was often to answer these types of questions: "Why did this particular frame fail Reed-Solomon decode? Why did this packet get marked as invalid? Why am I missing a block of telemetry from my query?" -- which are completely valid questions to ask from a GDS Engineer's point of view, and large families of tools have been designed to help answer these questions. But these are not the questions that most users care about - which are more like: "Why is the battery state of charge trending down? Show me a summary image report for the last traverse to the target. Show me a data accountability summary for the last DSN pass." Answers to these questions, which are what users are looking for, requires a higher level of abstraction and supporting tools than mining through ones and zeros. JPL has created a next generation capability called the Mission Data Processing and Control System (MPCS) which is designed to support this higher level of abstraction by providing customizable views of the ground system combining collections of lower level information into more meaningful ways. Instead of examining frames, packets, and individual telemetry data points -- MPCS is capable of providing comprehensive summary reports, product status, overall flight/ground event status, as well as payload health summaries. Based on these higher level views, end users can make tactical or strategic decisions, or drop into detailed analysis as needed. System designers need to continue building systems that support low level GDS troubleshooting - but the basic design of a GDS should be geared towards what end users actually need to see. This paper will describe the capabilities of MPCS that directly support these higher levels of abstraction, and which are being used today in missions such as the Mars Science Laboratory and other NASA missions.

MPCS↗

Search for charginos and neutralinos in final states with two boosted hadronically decaying bosons and missing transverse momentum in $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for charginos and neutralinos at the Large Hadron Collider using fully hadronic final states and missing transverse momentum is reported. Pair-produced charginos or neutralinos are explored, each decaying into a high-p T Standard Model weak boson. Fully hadronic final states are studied to exploit the advantage of the large branching ratio, and the efficient rejection of backgrounds by identifying the high-p T bosons using large-radius jets and jet substructure information. An integrated luminosity of 139 fb -1 of proton-proton collision data collected by the ATLAS detector at a center-of-mass energy of 13 TeV is used. No significant excess is found beyond the Standard Model expectation. Exclusion limits at the 95% confidence level are set on wino or higgsino production with various assumptions about the decay branching ratios and the type of lightest supersymmetric particle. A wino (higgsino) mass up to 1060 (900) GeV is excluded when the lightest supersymmetry particle mass is below 400 (240) GeV and the mass splitting is larger than 400 (450) GeV. The sensitivity to high-mass winos and higgsinos is significantly extended relative to previous LHC searches using other final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A New Appraisal- Lessons from the History of Efforts to Value Green and High-Performance Home Attributes in the United States

Rigorous consideration of green and high-performance (“green/HP”) features is rarely included in the property valuation process._ To help illuminate why this is the case, this report takes stock of the history of efforts to improve practices, and identifies barriers that have emerged and opportunities for overcoming them. Particular emphasis is placed on what energy and environmental policymakers and other stakeholders outside the appraisal community can contribute to the broader effort to advance professional practices. The history has unfolded in parallel with turbulent periods in the housing market for which appraisers and their customers are deemed to share responsibility, followed by cycles of regulations, siloing of appraisers in the name of professional integrity, and commoditization of the valuation process itself. This pattern has important ramifications for aspirations that appraisers engage more fully in identifying and valuing the green/HP characteristics of homes. On the one hand, it is legally and ethically incumbent on appraisers to do so, yet on the other hand it is perceived as a risky avenue to follow. Risks arise where findings can be challenged as either over- or under-stating value, together with a market environment in which the complexity of their assignments increases despite downward pressure on appraiser fees. While efforts to address green/HP considerations date back to the early 1980s, the vast majority of activity has taken place within the past five years. Many players have engaged in the efforts to promote improved valuation practices. These include the Appraisal Foundation, The Appraisal Institute, Colorado Energy Office, Earth Advantage, EcoBroker, Elevate Energy, Fannie Mae, Federal Housing Administration, Home Innovation Research Labs, The Institute for Market Transformation, Northwest Energy Efficiency Alliance, National Association of Homebuilders, National Association of State Energy Officials, National Association of Appraisers, RESNET, USEPA, USDOE and its National Laboratories, the U.S. Green Buildings Council, and the Vermont Green Homes Alliance. Many activities have resulted, ranging from trainings, to data-gathering instruments, and the emergence of a literature attempting to statistically isolate the effects of green/HP characteristics on home values. In some cases, the results of studies have been overgeneralized and oversold, and embodied flawed methods. Although the green/HP community has encouraged appraisers to focus on exemplary buildings (e.g., LEED or ENERGY STAR Certified), any level of green or energy performance can in fact influence value, including below-average performance (a.k.a. “brown discount”), irrespective of whether or not the building has been formally rated. This overly narrow focus represents a significant missed opportunity. Other surmountable challenges include limitations to non-appraisers’ understanding of the appraisal process (and practical constraints therein). A byproduct of this can be unrealistic expectations of what appraisers can and will do in the marketplace. These challenges notwithstanding, the environment for moving forward has improved. There is better data today (a critical need); expanded efforts to disclose energy use information (characteristics, consumption, bills); improved and more pervasive building energy codes, building rating and labeling initiatives; and a host of federal, state, and local policies that have collectively brought green/HP practices much more into the mainstream. Meanwhile, a renewed focus on professional standards of care and competency for assessing green/HP homes make it increasingly important for appraisers to consider these factors in their assignments. Despite the past four decades of studies, there is little if any discernible uptake of these practices by the appraisal practice at large. It would behoove interested parties to step back and consider what new strategies might be productive. A key element of any new plan should be to reset the nature of interactions with the industry, with the goal a more collaborative, two-way discussion to help improve outsiders’ understanding of the valuation process. It is not only the appraiser that needs to be engaged and could benefit from awareness raising. Homeowners, builders, lenders, utilities, insurance companies should also provide input on how green/HP factors impact property valuations and ways to accurately reflect these considerations in appraisals and real estate transactions more broadly. Given extensive inertia within the appraisal industry and a mixed history of interactions with the non-appraisal stakeholders, it is unlikely that the status quo will achieve much unless followed with more coordinated and persistent efforts. Workshops, studies, and memoranda of understanding will not on their own have much impact, and do not address deeper structural issues. Expectations are often unrealistic and not attentive to real-world constraints faced by appraisers. The report identifies key barriers impeding more thorough consideration of green/HP factors in residential real estate appraisals, and solutions for mitigating them. Barriers • Although industry standards of practice caution against bias of any sort, a skeptical predisposition towards “green” is reinforced by information deficiencies. • Information deficiencies result from the lack or difficulty of obtaining usable data on green/HP features in subject properties as well as valid sales comparisons or cashflow analyses. • Competency deficiencies, such as lack of conversancy in relevant technical topics, leads to oversights, and disjointed treatment of relevant information. • Time/cost pressure and process commoditization (e.g., template-based approaches) result from highly constrained budgets, quick turn-around times expected of appraisers, and standardized practices that were not developed with green/HP considerations in mind. • Professional differences between appraisers and sustainability professionals include divergent objectives, the former being market observers and the latter market influencers. • Risk aversion arises from multiple concerns including veracity, accuracy, and persistence of energy data, impacts of operational choices, new sources of appraiser liability associated with green/HP assessments, industry pressures not to over-value buildings or suggestion of bias, and concern about spending non-billable time on complex assignments. • A public policy vacuum has been created by disjointed and uncoordinated efforts from public-sector stakeholders, insufficient efforts to discuss and understand the appraisal industry and process, and a perception by some valuation professionals that green/HP is oversold. Opportunities • Elevating the competency of appraisers can be achieved through a combination of improved industry standards of care and equal-access training and professional development offerings. • Development of better information resources must focus on building-level information that provides robust documentation as well as aggregate sales-comparison data and other contextual information such as local codes, typical upgrade costs, energy prices, etc. • Improved energy benchmarking and rating tools could provide appraisers with information more well-adapted to their particular needs, which differ from those of typical audiences such as energy managers. • Better characterizing and managing risk will enable appraisers to cope with uncertainties in performance information, and help identify where risks may be introduced or mitigated by green/HP features, including higher costs or obsolescence of poorly-performing buildings. • Integrating disaster resilience and sustainability in appraisals would recognize important synergisms among these features, including durability and ability of green/HP buildings to better withstand external hazards. • Mitigating the problem of additional time/cost for performing assignments is an essential need that can be addressed by providing easier access to information and analytic procedures, perhaps coupled with new resources to defray the associated costs. • Enhancing demand for improved appraisals is a fundamental need, and depends on owners, developers, lenders, and others soliciting competent appraisers to perform scopes that expressly call out green/HP considerations, and to critically review the work product for compliance before acceptance. • Engaging new market participants, such as energy utilities and insurance companies can ensure fuller representation and participation of market stakeholders already engaged in green/HP activities and capable of furnishing valuable data and managing associated risks. Cutting across these individual activities, there is a need for outside stakeholders to formulate and follow a roadmap instead of piecemeal initiatives, bridging the professional/cultural divide between appraisers and green/HP communities, and tracking progress in order to know what is working. A more coherent communication and training strategy is needed, as the appraisal industry is highly fragmented, with two-thirds of appraisers opting out of membership in trade associations. In sum, while there is no silver bullet for advancing the practice of valuing green/HP features, there are concrete opportunities. Parties seeking solutions must identify barriers they wish to address and select from among potential initiatives that map to those barriers. Close collaboration with the appraisal community is critical, as non-appraisers have historically obtained limited traction with this industry due to lack of understanding of the nuances involved in the valuation profession. Large organizations and agencies should have a united approach; the perception or reality of a fragmented and uncoordinated strategy is unsettling for prospective partners in the appraisal industry. This requires improved communication and education within and among these communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

BOREAS RSS-14 Level-2 GOES-7 Shortwave and Longwave Radiation Images

The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. This data set contains images of shortwave and longwave radiation at the surface and top of the atmosphere derived from collected GOES-7 data. The data cover the time period of 05-Feb-1994 to 20-Sep-1994. The images missing from the temporal series were zero-filled to create a consistent sequence of files. The data are stored in binary image format files. Due to the large size of the images, the level-1a GOES-7 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1a GOES-7 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗

Simulator Evaluation of Airborne Information for Lateral Spacing (AILS) Concept

The Airborne Information for Lateral Spacing (AILS) concept is designed to support independent parallel approach operations to runways spaced as close as 2500 ft. This report describes the AILS operational concept and the results of a ground-based flight simulation experiment of one implementation of this concept. The focus of this simulation experiment was to evaluate pilot performance, pilot acceptability, and minimum miss-distances for the rare situation in which all aircraft oil one approach intrudes into the path of an aircraft oil the other approach. Results from this study showed that the design-goal mean miss-distance of 1200 ft to potential collision situations was surpassed with an actual mean miss-distance of 2236 ft. Pilot reaction times to the alerting system, which was an operational concern, averaged 1.11 sec, well below the design-goal reaction time 2.0 sec.These quantitative results and pilot subjective data showed that the AILS concept is reasonable from an operational standpoint.

Abbott, Terence S.↗

UAS Air Traffic Controller Acceptability Study: Evaluating Detect and Avoid Technology and Communication Delays in Simulation - 2

This study evaluated the effects of communications delays and winds on air traffic controller ratings of acceptability of horizontal miss distances (HMDs) for encounters between Unmanned Aircraft Systems (UAS) and manned aircraft in a simulation of the Dallas-Ft. Worth (DFW) airspace. Fourteen encounters per hour were staged in the presence of moderate background traffic. Seven recently retired controllers with experience at DFW served as subjects. Guidance provided to the UAS pilots for maintaining a given HMD was provided by information from Detect and Avoid (DAA) self-separation algorithms (Stratway+) displayed on the Multi-Aircraft Control System. This guidance consisted of amber "bands" on the heading scale of the UAS navigation display indicating headings that would result in a loss of well clear between the UAS and nearby traffic. Winds tested were successfully handled by the DAA algorithms and did not affect the controller acceptability ratings of the HMDs. Voice communications delays for the UAS were also tested and included one-way delay times of 0, 400, 1200, and 1800 msec. For longer communications delays, there were changes in strategy and communications flow that were observed and reported by the controllers. The aim of this work is to provide useful information for guiding future rules and regulations applicable to flying UAS in the NAS. Information from this study will also be of value to the Radio Technical Commission for Aeronautics (RTCA) Special Committee 228 - Minimum Performance Standards for UAS.

Comstock, James R., Jr.↗

Recent Improvements in the National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) has significantly evolved since the first release of the point source database in 1993. The NSRDB has been widely used by the solar energy industry to provide long-term time-series solar resource data for various project phases. The NSRDB represents the state of the art in the satellite-based estimation of solar resource information and uses a unique physics-based modeling approach that allows improvements in accuracy with the deployment of the next-generation geostationary satellites. This poster provides an overview of (1) the improved spatiotemporal resolution; (2) on-demand services and their applications; (3) future Improvements, such as a new direct normal irradiance model and new methods to gap-fill missing data using physics-guided machine learning; (4) data quality; and (5) data dissemination.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗

Analyses Made to Order: Using Transformation to Rapidly Configure a Multidisciplinary Environment

Aerospace problems are highly multidisciplinary. Four or more major disciplines are involved in analyzing any particular vehicle. Moreover, the choice of implementation technology of various subsystems can lead to a change of leading domain or reformation of the driving equations. An excellent example is the change of expertise required to consider aircraft built from composite or metallic structures, or those propelled by chemical or electrical thrusters. Another example is in the major reconfiguration of handling and stability equations with different control surface configuration (e.g., canards, t-tail v four-post tail). Combinatorial problems are also commonplace anytime that a major system is to be designed. If there are only 5 attributes of a design to consider with 4 different options, this is already 1024 options. Adding just 5 more dimensions to the study explodes the space to over one million. Even generous assumptions like the idea that only 10% of the combinations are physically feasible can only contain the problem for so long. To make matters worse, the simple number of combinations is only the beginning. Combining the issue of trade space size with the need to reformulate the design problem for many of the possibilities makes life exponentially more difficult. Advances in software modeling approaches have led to the development of model-driven architecture. This approach uses the transformation of models into inferred models (e.g. inferred execution traces from state machines) or the skeletons for code generation. When the emphasis on transformation is applied to aerospace, it becomes possible to exploit redundancy in the information specified in multiple domain models into a unified system model. F1urther, it becomes possible to overcome the combinatorial nature of specifying integrated system behavior by manually combining the equations governing a given component technology. Transformations from a system specification combined with a system-analysis mapping specification enable one-click combination of domain analyses. This is a flexibility that has been missing from many engineering codes, which often entangle design specification and physical examination much more than is required to conduct the analysis. This capability has been investigated and cultivated within the DARPA F6 program by a team of JPL and Phoenix Integration engineers building the Adapatable Systems Design and Analysis (ASDA) framework. By embracing system modeling with SysML and the Query-View-Transformation (QVT) language, the ASDA team has been able to build a flexible, easily reconfigurable framework for building up and solving large tradespaces. Examples of application and lessons learned in building the framework will be described in this paper. In addition, the motivation will be laid for various tool vendors to develop open model description standards while being able to maintain competitive advantage through proprietary algorithms and approaches. These standards will also be compared to the underpinnings of model-driven architecture and the OMG standards of the Meta-Object Facility (MOF), SysML, and QVT.

Cole, Bjorn↗

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗

Sci-Fri AM: Quality, Safety, and Professional Issues 06: An Evaluation of Incident Reporting and Learning using the Canadian National System for Incident Reporting – Radiation Treatment

We report on the development and clinical deployment of an in-house incident reporting and learning system that implements the taxonomy of the Canadian National System for Incident Reporting – Radiation Treatment (NSIR-RT). In producing our new system, we aimed to: Analyze actual incidents, as well as potentially dangerous latent conditions. Produce recommendations on the NSIR-RT taxonomy. Incorporate features to divide reporting responsibility among clinical staff and expedite incident categorization within the NSIR-RT framework. Share anonymized incident data with the national database. Our multistep incident reporting workflow is focused around an initial report and a detailed follow-up investigation. An investigator, chosen at the time of reporting, is tasked with performing the investigation. The investigation feature is connected to our electronic medical records database to allow automatic field population and quick reference of patient and treatment information. Additional features include a robust visualization suite, as well as the ability to flag incidents for discussion at monthly Risk Management meetings and task ameliorating actions to staff. Our system was deployed into clinical use in January 2016. Over the first three months of use, 45 valid incidents were reported; 31 of which were reported as actual incidents as opposed to near-misses or reportable circumstances. However, we suspect there is ambiguity within our centre in determining the appropriate event type, which may be arising from the taxonomy itself. Preliminary trending analysis aided in revealing workflow issues pertaining to storage of treatment accessories and treatment planning delays. Extensive analysis will be undertaken as more data are accrued.

60 APPLIED LIFE SCIENCES↗

Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors

Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals’ health and ultimately the consequences of anthropogenic stressors on populations.

59 BASIC BIOLOGICAL SCIENCES↗