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At least 379 records · Page 21

Modeling the asynchronous Jacobi method without communication delays

Asynchronous iterative methods for solving linear systems are gaining renewed interest due to the high cost of synchronization points in massively parallel codes. Historically, theory on asynchronous iterative methods has focused on asymptotic behavior, while the transient behavior remains poorly understood. In this paper, we study a model of the asynchronous Jacobi method without communication delays, which we call simplified asynchronous Jacobi. Simplified asynchronous Jacobi can be used to model asynchronous Jacobi implemented in shared memory or distributed memory with fast communication networks. Our analysis uses the idea of a propagation matrix, which is similar in concept to an iteration matrix. We show that simplified asynchronous Jacobi can continue to reduce the residual when some processes are slower than other processes. We also show that simplified asynchronous Jacobi can converge when synchronous Jacobi does not. We verify our analysis of simplified asynchronous Jacobi using results from asynchronous Jacobi implemented in shared and distributed memory.

97 MATHEMATICS AND COMPUTING↗

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗

Mathematical approaches to secure in-vehicle networks

Modern vehicles rely on numerous small computers called electronic control units (ECUs) that continually communicate life-critical messages, e.g., wheel speeds and steering angle, through a few controller area networks (CANs). Originally designed as a closed network for the life of the vehicle, CAN protocol developed bereft of security features (e.g., authentication or encryption). For emission testing, updates, and other diagnostics, vehicle CANs are now physically accessible, but this comes with vulnerability to cyber attack. Mandatory on-board diagnostic ports (OBD-II) provide adversaries with direct access to the vehicle. Remote attacks, e.g., via Bluetooth or cellular connections, are possible but require deep expertise. In short, the critical networks for vehicle functionality are exposed to remote and local cyber attacks with little to no built-in defenses. Most notably, the infamous 2015 research of Miller and Valasek exhibited a remote takeover of a Jeep’s brakes resulting in a massive recall and ample media coverage.

97 MATHEMATICS AND COMPUTING↗

Towards a CAN IDS Based on a Neural Network Data Field Predictor

Modern vehicles contain a few controller area networks (CANs), which allow scores of on-board electronic control units (ECUs) to communicate messages critical to vehicle functions and driver safety. CAN provides a lightweight and reliable broadcast protocol but is bereft of security features. As evidenced by many recent research works, CAN exploits are possible both remotely and with direct access, fueling a growing CAN intrusion detection system (IDS) body of research. A challenge for pioneering vehicle-agnostic IDSs is that passenger vehicles' CAN message encodings are proprietary, defined and held secret by original equipment manufacturers (OEMs). Targeting detection of next-generation attacks, in which messages are sent from the expected ECU at the expected time but with malicious content, researchers are now seeking to leverage "CAN data models'', which predict future CAN messages and use prediction error to identify anomalous, hopefully malicious CAN messages. Yet, current works model CAN signals post-translation, i.e., after applying OEM-donated or reverse-engineered translations from raw data. We present initial IDS results testing deep neural networks used to predict CAN data at the bit level, targeting IDS capabilities that avoiding reverse engineering proprietary encodings. Our results suggest the method is promising for data with signals exhibiting dependence on previous or concurrent inputs.

Pawelec, Krzysztof↗

Realistic model of entanglement-enhanced sensing in optical fibers

Experimental limitations such as optical loss and noise have prevented entanglement-enhanced measurements from demonstrating a significant quantum advantage in sensitivity. Holland-Burnett entangled states can mitigate these limitations and still present a quantum advantage in sensitivity. Here we model a fiber-based Mach-Zehnder interferometer with internal loss, detector efficiency, and external phase noise and without pure entanglement. This model features a practical fiber source that transforms the two-mode squeezed vacuum (TMSV) into Holland-Burnett entangled states. We predict that a phase sensitivity 28% beyond the shot noise limit is feasible with current technology. Simultaneously, a TMSV source can provide about 25 times more photon flux than other entangled sources. This system will make fiber-based quantum-enhanced sensing accessible and practical for remote sensing and probing photosensitive materials.

Krueper, Gregory↗

Energy Material Network Data Hubs

In early 2015 the United States Department of Energy conceived of a consortium of collaborative bodies based on shared expertise, data, and resources that could be targeted towards the more difficult problems in energy materials research. The concept of virtual laboratories had been envisioned and discussed earlier in the decade in response to the advent of the Materials Genome Initiative and similar scientific thrusts. To be effective, any virtual laboratory needed a robust method for data management, communication, security, data sharing, dissemination, and demonstration to work efficiently and effectively for groups of remote researchers. With the accessibility of new, easily deployed cloud technology and software frameworks, such individual elements could be integrated, and the required collaboration architecture is now possible. The developers have leveraged open-source software frameworks, customized them, and merged them into a platform to enable collaborative energy materials science, regardless of the geographic dispersal of the people and resources. After five years in operations, the systems are demonstratively an effective platform for enabling research within the Energy Material Networks (EMN). This paper will show the design and development of a secured scientific data sharing platform, the ability to customize the system to support diverse workflows, and examples of the enabled research and results connected with some of the Energy Material Networks.

97 MATHEMATICS AND COMPUTING↗

Field-deployable, nano-sensing approach for real-time detection of free mercury, speciation and quantification in surface stream waters and groundwater samples at the U.S. Department of Energy contaminated sites

The detrimental effects on human health caused by long-term exposure to trace contamination of toxic metals have been documented in numerous epidemiological and toxicological studies. The fact that metals are non-biodegradable and accumulate in the food chain poses a severe threat to the environment and human health. Their monitoring in drinking water, aquatic ecosystems, food and biological fluids samples is then essential for global sustainability. While research efforts employing established methodology continue to advance conceptual/computational models of contaminant behavior, the increasing awareness and public concern with environmental and occupational exposure to toxic metals calls for sensing devices capable to handle on-site elemental analysis in short analysis time. Field analysis with potable methodology prevents unnecessary scrutiny of un-contaminated samples via laboratory-bound methods, reduces analysis cost and expedites turnaround time for decision making and remediation purposes. Of particular toxicological interest are mercury and its species. Mercury is recognized as a major environmental pollution issue. The field-portable sensor developed in this project provides a unique and valuable tool for the on-site, real-time determination of inorganic mercury in surface waters. The ability to perform on-site analysis of mercury should prove useful in remote locations with difficult accessibility. It should facilitate data collection from statistically meaningful population sizes for a better understanding of the dose-effect role and the water-soil-plant-animal-human transfer mechanisms. The acquired knowledge should benefit the development of efficient environmental remediation processes, which is extremely relevant for a globally sustainable environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

SCRES Energy Quest Workshop (Technical Report)

Energy Quest: Sitka’s Path to 2050 is a game based public engagement tool developed as part of the Sitka Community Renewable Energy Strategy and the U.S. Department of Energy’s Energy Transitions Initiative Partnership Project Cohort 3. Designed for Sitka’s isolated island microgrid, which is powered primarily by hydropower and depends on imported diesel for backup, the game translated complex long term energy planning questions into an interactive format. In facilitated workshops, residents built energy roadmaps to 2050, explored tradeoffs, and expressed priorities around four themes: affordability, reliability, self sufficiency, and innovation. Across sessions, participants showed strong support for increasing local self sufficiency and resilience, even when this required balancing near term affordability with long term investments. They emphasized reducing dependence on imported diesel, making better use of existing hydropower, and considering new renewable generation such as solar, wind, and additional hydropower. Survey and game responses also highlighted interest in using surplus hydropower to support new industries, expanding electrification of heating and transportation, and exploring emerging technologies and green fuels. The report organizes these findings into four scenario themes to guide Sitka’s 2050 energy planning. Affordability focuses on managing rate impacts, efficiency, and conservation. Reliability addresses diversified generation, backup power, and energy security. Self sufficiency emphasizes distributed generation and reduced reliance on imported fuels. Innovation explores new technologies, marine based energy solutions, and low carbon fuels. By grounding future planning in these community derived themes, Energy Quest shows how a game based approach can make technical energy planning more accessible and inclusive for remote communities. For questions about the game board and piece production email Dr. Sarah Troise (sarah.troise@pnnl.gov)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Using Energy Storage-Based Grid Forming Inverters for Operational Reserve in Hybrid Diesel Microgrids

In remote arctic communities, where access to a bulk electrical grid interconnection is not available, the implementation of islanded microgrids has been the most viable way to produce and distribute electricity services to their inhabitants. Historically, these islanded grids have relied primarily on diesel generators or hydropower resources to supply the baseload. However, this practice can result in increased expense due to the high costs associated with fuel transportation and the significant amounts of on-site storage necessary when fuel transportation is unavailable during winter months. In order to mitigate this problem, arctic microgrids have started to transition to a hybrid-source operational mode by incorporating renewable energy sources that are inherently variable in nature, such as wind or solar. Due to their highly stochastic behavior, these hybrid-source islanded microgrids can pose potential issues related to power quality due to introduction of rapid net load fluctuations and inability of diesel generators to respond rapidly. In addition, non-firm stochastic sources can require significant idling diesel generator resources to serve as spinning reserves, which is inefficient and wasteful. This work studies the problems that may arise in the transient dynamics of a real-world hybrid diesel microgrid when subjected to a loss of wind generation. Moreover, this work proposes a transition from a diesel spinning reserve to a battery energy-storage system (BESS) operating reserve scheme. The study of the proposed transition is important in establishing the fundamental implication of transient dynamics and the potential benefits of integrating a BESS as a spinning reserve in terms of stability, frequency nadir, and transient voltage deviation. The methods to investigate and validate the transient dynamics relied on both electromagnetic simulation models of GFMIs and a commercially available GFMI in an experimental power hardware-in-the-loop setup. The simulation results showed that the proposed operating reserve scheme improves the power quality of the system in terms of voltage deviation and frequency nadir when the microgrid is subjected to a loss of wind generation scenario. Depending on the simulation cases, adding a GFMI reduced the frequency nadir between 65.3% and 86.7%. Moreover, the reductions in the voltage deviations improved between 3.6% and 23.0%. From these results it can be concluded that the integration of a GFMI can reduce the frequency nadir in a hybrid diesel microgrid, and in turn, reduce diesel consumption, which improves system reliability while reducing fuel expenses. Furthermore, the novelty of this work relies on the fact that the offline simulation results were validated using a power hardware-in-the-loop platform that incorporated a 100 kVA commercially available GFMI as the device under test.

Hernandez-Alvidrez, Javier↗

The 1970/71 spectral data management programs

The data management programs used by the Stanford Remote Sensing Laboratory to access, modify, and reduce the data obtained from both the NASA IR airborne spectrometer, and Stanford's SG-4 field spectrometer are reported. Many details covered in previous reports are not repeated. References are provided. These programs are written in FORTRAN 4 and S/360 Assembler Language, and are currently running on a S/360 model 67 (operating under OS/MFT) at the Stanford Computation Center Campus Facility.

Marshall, A. A.↗

Ozone monitoring with an infrared heterodyne radiometer

Measurements of the total burden and of the concentration-versus-altitude profiles of ozone have been made with a ground-based heterodyne radiometer at Pasadena, California. The measurements were made in the 9.5-micron wavelength region, where a strong ozone infrared absorption band exists. The radiometer measured solar absorption at selected wavelengths with a spectral resolution of 0.001 reciprocal centimeter, equivalent to the half-width of an ozone absorption line at the 10-millibar altitude level. A carbon dioxide laser served as the local oscillator. This technique can be used to gather important data on both tropospheric and stratospheric ozone, which are not readily accessible with other remote-sensing techniques.

Menzies, R. T.↗

An integrated user-oriented laboratory for verification of digital flight control systems: Features and capabilities

A Digital Flight Control Systems Verification Laboratory (DFCSVL) has been established at NASA Ames Research Center. This report describes the major elements of the laboratory, the research activities that can be supported in the area of verification and validation of digital flight control systems (DFCS), and the operating scenarios within which these activities can be carried out. The DFCSVL consists of a palletized dual-dual flight-control system linked to a dedicated PDP-11/60 processor. Major software support programs are hosted in a remotely located UNIVAC 1100 accessible from the PDP-11/60 through a modem link. Important features of the DFCSVL include extensive hardware and software fault insertion capabilities, a real-time closed loop environment to exercise the DFCS, an integrated set of software verification tools, and a user-oriented interface to all the resources and capabilities.

Defeo, P.↗

Recommendations concerning satellite-acquired earth resource data: 1982 report of the Data Management Subcommittee of the GEOSAT Committee, Incorporated

End user concerns about the content and accessibility of libraries of remote sensing data in general are addressed. Recommendations pertaining to the United States' satellite remote sensing programs urge: (1) the continuation of the NASA/EROS Data Center program to convert pre-1979 scenes to computer readable tapes and create a historical archive of this valuable data; (2) improving the EROS archive by adding geologically interesting scenes, data from other agencies (including previously classified data), and by adopting a policy to retire data from the archive; (3) establishing a computer data base inquiry system that includes remote sensing data from all publically available sources; (4) capability for prepurchase review and evaluation; (5) a flexible price structure; and (6) adoption of standard digital data products format. Information about LANDSAT 4, the status of worldwide LANDSAT receiving stations, future non-U.S. remote sensing satellites, a list of sources for LANDSAT data, and the results of a survey of GEOSAT members' remote sensing data processing systems are also considered.

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Science on the Space Station: The opportunity and the challenge - A NASA view

The Science and Applications Information System (SAIS) which will provide users with remote, interactive, and iterative access from their home locations to the many information system services is introduced. Such aspects as transaction management, standard format data units, and the use of intelligent data management systems are discussed. It is concluded that new and innovative approaches to information management must be developed so that the full potential of the Space Station can be realized with respect to the demands of the entire science community.

Devirian, Michael↗

Numerical Aerodynamic Simulation Program

Report describes developments that occurred at National Aerodynamics Simulation (NAS) facility at Ames Research Center during years 1987 and 1988. Begins with description of NAS processing network, which is large network of computers. Followed by summary of early achievements of program and advanced features of network, including installation of supercomputers, installation of standard operating system and communication software on all processors, accessibility to users at remote facilities across United States, and emphasis on development of graphics workstations to display results of numerical simulation.

Bailey, F. R.↗

Titan Airship Surveyor

Saturn's moon Titan is considered to be one of the prime candidates for studying prebiotic materials - the substances that precede the formation of life but have disappeared from the Earth as a result of the evolution of life. A unique combination of a dense, predominantly nitrogen, atmosphere (more than four times that of the Earth), low gravity (six times less than on the Earth) and small temperature variations makes Titan the almost ideal planet for studies with lighter-than-air aerial platforms (aerobots). Moreover, since methane clouds and photochemical haze obscure the surface, low-altitude aerial platforms are the only practical means that can provide global mapping of the Titan surface at visible and infrared wavelengths. One major challenge in Titan exploration is the extremely cold atmosphere (approx. 90 K). However, current material technology the capability to operate aerobots at these very low temperatures. A second challenge is the remoteness from the Sun (10 AU) that makes the nuclear (radioisotopic) energy the only practical source of power. A third challenge is remoteness from the Earth (approx. 10 AU, two-way light-time approx. 160 min) which imposes restrictions on data rates and makes impractical any meaningful real-time control. A small-size airship (approx. 25 cu m) can carry a payload approximately 100 kg. A Stirling engine coupled to a radioisotope heat source would be the prime choice for producing both mechanical and electrical power for sensing, control, and communications. The cold atmospheric temperature makes Stirling machines especially effective. With the radioisotope power source the airship may fly with speed approximately 5 m/s for a year or more providing an excellent platform for in situ atmosphere measurements and a high-resolution remote sensing with unlimited access on a global scale. In a station-keeping mode the airship can be used for in situ studies on the surface by winching down an instrument package. Floating above the surface allows relatively simple means for flight control. Mission requirements and possible methods of navigation, control, data acquisition, and communications are discussed. The presentation describes also the state-of-the art and current progress in aerial deployed aerobots.

Kerzhanovich, V.↗

[Earth Sciences Research]

contents include the following: 1. Argentina Field Expedition (2004). NASA funds supported joint fieldwork by Peter Makovicky (Dept. of Geology, TFM) and Sebastian Apesteguia (Museo Argentino de Ciencias Naturales, Buenos Aires) in a fossil-rich locality in the Cenomanian Candeleros Formation of northern Rio Negro Province, Argentina. The goal of this fieldwork was to collect small fossil vertebrates, which are abundant in this formation, with a special emphasis on small theropod (casmivorous) dinosaurs. 2. East Greenland Field Expedition (2004). During July-August 2004 the Field Museum led a month long expedition to Jameson Land in East Greenland to collect Triassic-Jurassic aged fossil plants from one of the most productive sites of this age in the world. The project aims include the study of events leading up to catastrophic changes in the biota and atmosphere that occurred about 200 million years ago. 3. Chile Field Expedition (March, 2004). Paleontological reconnaisance of the central Andean main range by helicopter: additional new Cenozoic mammal faunas from Chile. A several thousand sq km swath of the central Andean Cordillera was prospected by helicopter during 2004, permitting rapid survey of large areas in remote or difficult to access regions. This led to the recovery of fossils from several parts of the range, and the identification of sites worthy of future attention. 4. Wyoming Field Expedition (2004). NASA funds supported a three-week field program by Curator of Dinosaurs Peter Makovicky and a crew of Field Museum staff and volunteers at several sites in the Early Cretaceous Cloverly Formation of north-central Wyoming. The nine-member team excavated a number of sites that had been discovered over the preceding two summers.

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