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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Analysis Facilities for HL-LHC

The HL-LHC presents significant challenges for the HEP analysis community. The number of events in each analysis is expected to increase by an order of magnitude and new techniques are expected to be required; both challenges necessitate new services and approaches for analysis facilities. These services are expected to provide new capabilities, a larger scale, and different access modalities (complementing -- but distinct from -- traditional batch-oriented approaches). To facilitate this transition, the US-LHC community is actively investing in analysis facilities to provide a testbed for those developing new analysis systems and to demonstrate new techniques for service delivery. This whitepaper outlines the existing activities within the US LHC community in this R&D area, the short- to medium-term goals, and the outline of common goals and milestones.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The Effect of Laser Cutting Heuristic Presentation Modality on Design Learning

Abstract The goal of this work is to study the way student designers use heuristics to effectively design for laser-cut manufacturing methods. With the recent advent of academic makerspaces, digital fabrication tools like laser cutters are relatively new additions to the classroom. Therefore, there is a gap in formal education or training on these tools, and students can find it challenging to design effectively for them. A study was performed to investigate the way students apply heuristics to redesign laser-cut assemblies when received in different modalities. All participants were given an identical lecture on laser cutting heuristics. Then, a redesign problem was presented to students, and three different experimental groups were given the heuristics in different modalities: Text-Only, text with Visual aids, and text with Tactile aids. The novelty and quality of each of the resulting redesigns were evaluated. It was hypothesized that participants would have more difficulty interpreting and applying the Text-Only heuristics, lowering the quality of their redesigned solutions relative to the other two conditions. It was also hypothesized that participants would experience fixation caused by interacting with the tactile aids, leading to the lower novelty of their redesigned solutions relative to the other two conditions. Results showed that modality played a significant role in participants’ feelings of self-efficacy after the intervention, as well as in their understanding of laser cutter design skills when responding to quiz-style questions. However, analysis of novelty and quality showed little significant impact of the intervention and varying modalities on participants’ designs.

Engineering↗
DOE OSTI2025

Unimodal Imaging of Monovalent Metal-Chelator Complexes and Lipids by MALDI Imaging Mass Spectrometry

Careful regulation of monovalent metal ions (M + ) is necessary to maintain a functional cellular system. Of these ions, appropriate sodium (Na + ) and potassium (K + ) concentrations are particularly integral for electrochemical signaling, as well as the secondary transport of nutrients and waste. Dysregulation of M + homeostasis can disrupt these mechanisms, potentially influencing the metabolism of downstream biomolecules such as lipids. Thus, the relationship between M + abundances and related biomolecular distributions must be elucidated to better understand the physiology of healthy and disordered tissues. Traditional techniques for imaging biological metal distributions include SIMS, LA-ICP-MS, and XRF; however, these capabilities are limited to elemental analysis or the analysis of molecular fragments and must be paired with other modalities to visualize distributions of more complex biomolecules within the same or similar samples. Conversely, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool often used for mapping such biomolecular distributions, but current methods are unable to detect metals within tissue. This study illustrates a novel methodology that adds metal detection to the MALDI IMS repertoire through which the simultaneous detection of M + metals and lipids is achievable. Using a robotic sprayer for homogeneous application, on-tissue deposition of the chelator deferiprone (DEF) enables subsequent detection of the ionizable metal-chelator complex by MALDI without hindering lipid detection. Our work provides proof-of-concept data for the simultaneous detection of K + , Na + , and intact lipids using MALDI IMS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Size and Time-Resolved Automated Aerosol Sampling Field Campaign Report

To improve the understanding of the impacts of the vertical distribution of aerosol chemical composition on radiative forcing of aerosol, we performed a detailed physicochemical characterization of aerosol particles sampled during ARM deployment of the tethered balloon system at two ARM sites. We used multi-modal microscopy/spectroscopy techniques and advanced mass spectrometry platforms for the analysis of particles. We found variations in size-resolved aerosol composition at different altitudes. We also observed changes in aerosol composition during different seasons. Some of our observations at ARM’s Oliktok Point, Alaska site suggest cloud processing of aerosol while sampling in clouds, below clouds, and above clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A prototype scintillator real‐time beam monitor for ultra‐high dose rate radiotherapy

Background: FLASH Radiotherapy (RT) is an emergent cancer RT modality where an entire therapeutic dose is delivered at more than 1000 times higher dose rate than conventional RT. For clinical trials to be conducted safely, a precise and fast beam monitor that can generate out-of-tolerance beam interrupts is required. This paper describes the overall concept and provides results from a prototype ultra-fast, scintillator-based beam monitor for both proton and electron beam FLASH applications. Purpose: A FLASH Beam Scintillator Monitor (FBSM) is being developed that employs a novel proprietary scintillator material. The FBSM has capabilities that conventional RT detector technologies are unable to simultaneously provide: (1) large area coverage; (2) a low mass profile; (3) a linear response over a broad dynamic range; (4) radiation hardness; (5) real-time analysis to provide an IEC-compliant fast beam-interrupt signal based on true two-dimensional beam imaging, radiation dosimetry and excellent spatial resolution. Methods: The FBSM uses a proprietary low mass, less than 0.5 mm water equivalent, non-hygroscopic, radiation tolerant scintillator material (designated HM: hybrid material) that is viewed by high frame rate CMOS cameras. Folded optics using mirrors enable a thin monitor profile of ∼10 cm. A field programmable gate array (FPGA) data acquisition system generates real-time analysis on a time scale appropriate to the FLASH RT beam modality: 100–1000 Hz for pulsed electrons and 10–20 kHz for quasi-continuous scanning proton pencil beams. An ion beam monitor served as the initial development platform for this work and was tested in low energy heavy-ion beams ( 86 Kr +26 and protons). A prototype FBSM was fabricated and then tested in various radiation beams that included FLASH level dose per pulse electron beams, and a hospital RT clinic with electron beams. Results: Results presented in this report include image quality, response linearity, radiation hardness, spatial resolution, and real-time data processing. Furthermore, the HM scintillator was found to be highly radiation damage resistant. It exhibited a small 0.025%/kGy signal decrease from a 216 kGy cumulative dose resulting from continuous exposure for 15 min at a FLASH compatible dose rate of 237 Gy/s. Measurements of the signal amplitude versus beam fluence demonstrate linear response of the FBSM at FLASH compatible dose rates of >40 Gy/s. Comparison with commercial Gafchromic film indicates that the FBSM produces a high resolution 2D beam image and can reproduce a nearly identical beam profile, including primary beam tails. The spatial resolution was measured at 35–40 µm. Tests of the firmware beta version show successful operation at 20 000 Hz frame rate or 50 µs/frame, where the real-time analysis of the beam parameters is achieved in less than 1 µs. Conclusions: The FBSM is designed to provide real-time beam profile monitoring over a large active area without significantly degrading the beam quality. A prototype device has been staged in particle beams at currents of single particles up to FLASH level dose rates, using both continuous ion beams and pulsed electron beams. Using a novel scintillator, beam profiling has been demonstrated for currents extending from single particles to 10 nA currents. Radiation damage is minimal and even under FLASH conditions would require ≥50 kGy of accumulated exposure in a single spot to result in a 1% decrease in signal output. Beam imaging is comparable to radiochromic films, and provides immediate images without hours of processing. Real-time data processing, taking less than 50 µs (combined data transfer and analysis times), has been implemented in firmware for 20 kHz frame rates for continuous proton beams.

2D beam imaging↗
DOE OSTI2025

Evaluating the feasibility of LA-ICP-TOF-MS for the analysis of environmental particle collections

Laser ablation-inductively coupled plasma-time-of-flight-mass spectrometry (LA-ICP-TOF-MS) was employed to rapidly analyze environmental particle samples collected using aerosol contaminate extractors (ACE). The ACE particle collectors were placed at various distances (0.5, 1.3, and 4.5 km) from a source that released Ru-bearing particles. Samples for measurement were then generated (as sub-samples) from the ACE collection plates via particle “lift off” with gunshot residue (GSR) tabs. The LA-ICP-TOF-MS method was employed such that 10+ samples could be analyzed in a single unattended analytical session. A 3 × 1 mm area of individual GSR tab samples were analyzed in less than 30 minutes. This provided spatially resolved elemental and isotopic measurements of the particulate content and confirmed the presence of Ru-bearing particles within the complex background environmental particle loading. As anticipated, measurements showed collectors closest to the source had the highest concentration of the released Ru-bearing particles, while all collectors, regardless of distance, contained similar levels of background particles (e.g., Fe and Sr). Sequential scanning electron microscopy – automated particle analysis (SEM-APA) and LA-ICP-TOF-MS analysis was employed for method validation and a demonstration of the multi-modal approach. The same 2-dimensional region was analyzed by both methods and the particles identified via SEM-APA were also detected using LA-ICP-TOF-MS, with 100% accuracy. Overall, LA-ICP-TOF-MS demonstrated its utility for rapid elemental and isotopic particle analysis from environmental air samples.

Manard, Benjamin T. [Oak Ridge National Laboratory↗
DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗
DOE OSTI2025

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Fluid-Dynamic Mechanisms Underlying Wind Turbine Wake Control with Strouhal-Timed Actuation

A reduction in wake effects in large wind farms through wake-aware control has considerable potential to improve farm efficiency. This work examines the success of several emerging, empirically derived control methods that modify wind turbine wakes (i.e., the pulse method, helix method, and related methods) based on Strouhal numbers on the O(0.3). Drawing on previous work in the literature for jet and bluff-body flows, the analyses leverage the normal-mode representation of wake instabilities to characterize the large-scale wake meandering observed in actuated wakes. Idealized large-eddy simulations (LES) using an actuator-line representation of the turbine blades indicate that the n=0 and ±1 modes, which correspond to the pulse and helix forcing strategies, respectively, have faster initial growth rates than higher-order modes, suggesting these lower-order modes are more appropriate for wake control. Exciting these lower-order modes with periodic pitching of the blades produces increased modal growth, higher entrainment into the wake, and faster wake recovery. Modal energy gain and the entrainment rate both increase with streamwise distance from the rotor until the intermediate wake. This suggests that the wake meandering dynamics, which share close ties with the relatively well-characterized meandering dynamics in jet and bluff-body flows, are an essential component of the success of wind turbine wake control methods. A spatial linear stability analysis is also performed on the wake flows and yields insights on the modal evolution. In the context of the normal-mode representation of wake instabilities, these findings represent the first literature examining the characteristics of the wake meandering stemming from intentional Strouhal-timed wake actuation, and they help guide the ongoing work to understand the fluid-dynamic origins of the success of the pulse, helix, and related methods.

17 WIND ENERGY↗
DOE OSTI2026

NREL OpenPATH: An Open-Source, Extensible Platform for Instrumenting Travel Behavior Data

NREL OpenPATH is an open-source, extensible platform that allows communities to instrument their own travel behavior data. The platform consists of a smartphone app, server and analysis pipeline, and enables collection of opt-in, multi-modal, end-to-end travel diaries. It makes the aggregate statistics available via a public dashboard, and allows deployers to download and visualize trip and trajectory data through the admin dashboard. It also allows for customization of the initial demographic survey and the trip-level qualitative information collected. Our goal is to provide an easy-to-use tool that can democratize travel behavior data collection by empower communities of all sizes to recruit participants and obtain a holistic picture of their travel patterns. The platform has been used by close to 40 partners, to collect data from thousands of participants. Upon signing a simple MOU, it is currently available for free to universities, non-profits and public agencies in the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Density reconstruction in convergent high-energy-density systems using x-ray radiography and Bayesian inference

X-ray radiography is a technique frequently used to diagnose convergent high-energy-density (HED) systems, such as inertial confinement fusion implosion, and provides unique information that is not available through self-emission measurements. In this work, we investigate the scope and limits of that information using a radiography simulation combined with the Bayesian inference workflow. The accuracy of density reconstruction from simulated radiographs of spherical implosions driven with 27 kJ laser energy is assessed, including the increase or decrease in accuracy due to the addition of Lagrangian marker layers, Poisson noise, and improved prior information. This work is the first to present the full uncertainty distributions inferred from radiography analysis in HED systems and demonstrates the importance of constructing the full posterior probability density, as opposed to a point estimate, due to the modal structure of the likelihood surface introduced by typical experimental noise sources. This general methodology can be used both for robust analysis of radiographic data and for an improved design of radiography experiments by modeling the full experimental system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Understanding the Fluorination of Disordered Rocksalt Cathodes through Rational Exploration of Synthesis Pathways

Here, we have designed and tested several synthesis routes targeting a highly fluorinated disordered rocksalt (DRX) cathode, Li 1.2 Mn 0.4 Ti 0.4 O 1.6 F 0.4 , with each route rationalized by thermochemical analysis. Precursor combinations were screened to raise the F chemical potential and avoid the formation of LiF, which inhibits fluorination of the targeted DRX phase. MnF 2 was used as a reactive source of F, and Li 6 MnO 4 , LiMnO 2 , and Li 2 Mn 0.33 Ti 0.66 O 3 were tested as alternative Li sources. Each synthesis procedure was monitored using a multi-modal suite of characterization techniques including X-ray diffraction, nuclear magnetic resonance, thermogravimetric analysis, and differential scanning calorimetry. From the resulting data, we advance the understanding of oxyfluoride synthesis by outlining the key factors limiting F solubility. At low temperatures, MnF 2 consistently reacts with the Li source to form LiF as an intermediate phase, thereby trapping F in strong Li-F bonds. LiF can react with Li 2 TiO 3 to form a highly lithiated and fluorinated DRX (Li 3 TiO 3 F); however, MnO is not easily incorporated into this DRX phase. Although higher temperatures typically increase solubility, the volatility of LiF above its melting point (848 °C) inhibits fluorination of the DRX phase. Based on these findings, metastable synthesis techniques are suggested for future work on DRX fluorination.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Gamma-Ray and Cosmic Ray Muon Modalities for Cargo Inspection

Screening and inspection of cargo containers are two essential methods to nondestructively examine the contents of shipment. These methods enable the detection of illicit transportation of unauthorized materials such as nuclear and radioactive materials, explosives, drugs, and so on, typically at borders or secure facilities. Although high-energy X-ray transmission is a standard system and is widely used for cargo inspection, the inherent challenges of high false-positive rates and high attenuation factors necessitate the development of complementary techniques that can increase the detection efficiency and accuracy in large and dense materials. Gamma-rays, which possess higher penetration characteristics because of their high energy, offer an alternative nonintrusive modality for cargo scanning. They represent a promising inspection method when compared to X-rays for three reasons: (1) improved ability to detect nuclear and radioactive materials, (2) higher inspection throughput rates, and (3) lower false-positive rates. Currently, there are two main gamma-ray inspection techniques, active and passive interrogation. Active interrogation can be further grouped into (1) gamma-ray transmission imaging and (2) neutron-induced gamma-ray emission detection. Gamma-ray transmission imaging utilizes differences in material densities for mapping the shipment contents and detecting anomalies. It is analogous to the X-ray transmission method; however, the high-energy photons make it more difficult to shield against, which enables more efficient performance in large and dense material inspection. Neutron-induced gamma-ray emission inspection is designed for the detection of nuclear and radioactive material because those materials emit characteristic gamma-rays when they are activated by neutron absorption. On the other hand, passive interrogation techniques rely on high-efficiency detectors to detect radiation emitted from hidden special nuclear or other radioactive materials. Similar to passive interrogation, cosmic ray muon monitoring and imaging are relatively new techniques that do not require external radioactive sources. These techniques have received attention as a potential next-generation radiographic probe to identify illicit transportation of nuclear and radioactive materials in cargo containers. Cosmic ray muons have unique features, (1) much higher energies than X-rays or gamma-rays (on the order of 10−1—104 GeV), (2) enhanced penetration capability, and (3) natural occurrence, thereby eliminating the need for induced radiation sources. These features enable cosmic ray muons to be utilized for detection of special nuclear materials in high-background-noise environments. By analyzing incoming and outgoing muon trajectories, scattering angles, and energies, it has been shown that it would be possible to locate hidden and well-shielded materials in cargo containers via three-dimensional muon tomography images or signal analysis. Gamma-rays, cosmic ray muons, and other nonintrusive cargo inspection modalities are complementary to each other, allowing them to address various cargo inspection conditions (i.e., scanning time, cost, radiation exposure level, and types of target materials). This chapter presents a detailed review of the theoretical fundamentals and technical principles behind the current gamma-ray and cosmic ray muon modalities for cargo inspection. Additionally, critical assessments and suggestions for the future directions to advance the use of gamma and muon modalities are discussed.

Bae, Junghyun↗
DOE OSTI2021

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Interface instabilities in hafnium hydride entrained iron metal matrix composites

The chemical interactions in Fe–HfH 2 metal matrix composites (MMCs) are studied across multiple length scales to elucidate the decomposition of the parent phases and corresponding reaction zone physics during direct current sintering. Fe–HfH 2 composites were synthesized with increasing as-mixed hydride contents of Fe–25% HfH 2 , Fe–40% HfH 2 , Fe–55% HfH 2 , and Fe–70% HfH 2 (all in vol. %) to demonstrate the ability to achieve sintered MMCs with target hydride contents. Samples were probed across multiple length scales through a multi-modal workflow employing x-ray diffraction, scanning electron microscopy and segmentation analysis, and synchrotron techniques including hard x-ray fluorescence mapping and nanoprobe x-ray absorption near-edge structure measurements. Under the selected sintering temperature and pressure conditions, hydrogen evolution is seen to evolve through parallel paths: thermal decomposition from during the transformation of HfH 2 to HfH x<2 and through subsequent reaction with the Fe matrix leading to intermetallic phase formation. Specifically, HfFe and HfFe 2 intermetallic formation accelerates the release of hydrogen with a subsequent HfO 2 phase forming at grain boundaries. For this MMC, the consumption or loss of hydrogen can be considerable in compacts with initial hydride loading of 25%–40% HfH 2 approaching 83% hydrogen loss for the lower volume fraction composites. Increasing the volume fraction of HfH 2 to 70% enhanced the retained hydrogen content to 53% and attributed to the reduced interfacial area intrinsic to the increased HfH 2 loading in this MMC.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Neurodata Without Borders ecosystem for neurophysiological data science

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB’s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Involved-Field Radiation Therapy Prevents Recurrences in the Early Stages of Hodgkin Lymphoma in PET-Negative Patients After ABVD Chemotherapy: Relapse Analysis of GHSG Phase 3 HD16 Trial

The HD16 trial of the German Hodgkin Study Group (NCT00736320) demonstrated that radiation therapy in early-stage Hodgkin lymphoma without risk factors cannot be safely omitted, and therefore combined modality therapy (CMT) remains the standard treatment. To demonstrate the local effect of consolidating involved-field radiation therapy (IF-RT), we performed an analysis of the recurrence pattern of positron emission tomography (PET)-negative HD16 patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗