Results for “Spatial Generative Model” — Page 73

DOE OSTI2017

Convolutional Neural Network Approach for Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion

Accurate and high-resolution maps of vegetation are critical for projects seeking to understand the terrestrial ecosystem processes and land-atmosphere interactions in Arctic ecosystems, such as U.S. Department of Energy's Next Generation Ecosystem Experiment (NGEE) Arctic. However, most existing Arctic vegetation maps are at a coarse resolution and with a varying degree of detail and accuracy. Remote sensing-based approaches for mapping vegetation, while promising, are challenging in high latitude environments due to frequent cloud cover, polar darkness, and limited availability of high-resolution remote sensing datasets (e.g., ~ 5 m). This study proposes a new remote sensing based multi-sensor data fusion approach for developing high-resolution maps of vegetation in the Seward Peninsula, Alaska. We focus detailed analysis and validation study around the Kougarok river, located in the central Seward Peninsula of Alaska. We seek to evaluate the integration of hyper-spectral, multi-spectral, radar, and terrain datasets using unsupervised and supervised classification techniques over a ~343.72 km 2 area for generating vegetation classifications at a variety of resolutions (5 m and 12.5 m). We fist applied a quantitative goodness-of-fit method, called Mapcurves, that shows the degree of spatial concordance between the public coarse resolution maps and k-means clustering values and relabels the k values based on the best overlap. We develop a convolutional neural network (CNN) approach for developing high resolution vegetation maps for our study region in Arctic. We compare two CNN approaches: (1) breaking up the images into small patches (e.g., 6 × 6) and predict the vegetation class for entire patch and (2) semantic segmentation and predict the vegetation class for every pixel. We also perform accuracy assessments of the developed data products and evaluate varying CNN architectures. The fusion of hyperspectral and optical datasets performed the best, with accuracy values increased from 0.64 to 0.96-0.97 when using a training map produced by unsupervised clustering and Mapcurves labeling for both CNN models.

Langford, Zach↗

DOE OSTI2017

Simulations and measurements of hot-electron generation driven by the multibeam two-plasmon-decay instability

We report that multiple-beam experiments relevant to direct-drive inertial confinement fusion show the importance of nonlinear saturation mechanisms in the common-wave two-plasmon-decay (TPD) instability. Planar target experiments on the OMEGA laser used hard-x-ray measurements to study the influence of the linear common-wave growth rate on TPD driven hot-electron production in two drive beam configurations and over a range of overlapped laser intensities from 3.6 to 15.2 x 10 14 W/cm 2 . The beam configuration with the larger linear common-wave growth rate had a lower intensity threshold for the onset of hot-electron production, but the linear growth rate did not have a significant impact on hot-electron production at high intensities. The experiments were modeled in 3-D using a hybrid code (LPSE) that combines a wave solver with a particle tracker to self-consistently calculate the electron velocity distribution and evolve electron Landau damping. Finally, good quantitative agreement was obtained between the simulated and measured hotel-electron distributions using a novel technique to account for macroscopic spatial and temporal variations that are present in the experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model

Abstract. Emissions of anthropogenic aerosol and their precursors are often prescribed in global aerosol models. Most of these emissions are spatially heterogeneous at model grid scales. When remapped from low-resolution data, the spatial heterogeneity in emissions can be lost, leading to large errors in the simulation. It can also cause the conservation problem if non-conservative remapping is used. The default anthropogenic emission treatment in the Energy Exascale Earth System Model (E3SM) is subject to both problems. In this study, we introduce a revised emission treatment for the E3SM Atmosphere Model (EAM) that ensures conservation of mass fluxes and preserves the original emission heterogeneity at the model-resolved grid scale. We assess the error estimates associated with the default emission treatment and the impact of improved heterogeneity and mass conservation in both globally uniform standard-resolution (∼ 165 km) and regionally refined high-resolution (∼ 42 km) simulations. The default treatment incurs significant errors near the surface, particularly over sharp emission gradient zones. Much larger errors are observed in high-resolution simulations. It substantially underestimates the aerosol burden, surface concentration, and aerosol sources over highly polluted regions, while it overestimates these quantities over less-polluted adjacent areas. Large errors can persist at higher elevation for daily mean estimates, which can affect aerosol extinction profiles and aerosol optical depth (AOD). We find that the revised treatment significantly improves the accuracy of the aerosol emissions from surface and elevated sources near sharp spatial gradient regions, with significant improvement in the spatial heterogeneity and variability of simulated surface concentration in high-resolution simulations. In the next-generation E3SM running at convection-permitting scales where the resolved spatial heterogeneity is significantly increased, the revised emission treatment is expected to better represent the aerosol emissions as well as their lifecycle and impacts on climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗

DOE OSTI2021

Understanding magnetic phase coexistence in Ru 2 Mn 1-x Fe x Sn Heusler alloys: A neutron scattering, thermodynamic, and phenomenological analysis

The random substitutional solid solution between the antiferromagnetic (AFM) full-Heusler alloy Ru 2 MnSn and the ferromagnetic (FM) full-Heusler alloy Ru 2 FeSn provides a rare opportunity to study FM-AFM phase competition in a near-lattice-matched, cubic system, with full solubility. At intermediate x in Ru 2 Mn 1-x Fe x Sn this system displays suppressed magnetic ordering temperatures, spatially coexisting FM and AFM order, and strong coercivity enhancement, despite rigorous chemical homogeneity. Here, we construct the most detailed temperature- and x-dependent understanding of the magnetic phase competition and coexistence in this system to date, combining wide-temperature-range neutron diffraction and small-angle neutron scattering with magnetometry and specific heat measurements on thoroughly characterized polycrystals. A complete magnetic phase diagram is generated, showing FM-AFM coexistence between x ≈ 0.30 and x ≈ 0.70. Furthermore, important insight is gained from the extracted length scales for magnetic phase coexistence (25–100 nm), the relative magnetic volume fractions and ordering temperatures, and remarkable x-dependent trends in magnetic and electronic contributions to specific heat. An unusual feature in the magnetic phase diagram (an intermediate FM phase) is also shown to arise from an extrinsic effect related to a minor Ru-rich secondary phase. The established magnetic phase diagram is then discussed with the aid of phenomenological modeling, clarifying the nature of the mesoscale phase coexistence with respect to the understanding of disordered Heisenberg models.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Diagnostics, Control and Performance Parameters for the BELLA High Repetition Rate Petawatt Class Laser

A laser system producing controllable and stable pulses with high power and ultrashort duration at high repetition rate is a key component of a high energy laser-plasma accelerator (LPA). Precise characterization and control of laser properties are essential to understanding laser-plasma interactions required to build a 10-GeV class LPA. This study discusses the diagnostics, control and performance parameters of a 1 Hz, 1 petawatt (PW) class laser at the Berkeley Lab Laser Accelerator (BELLA) facility. The BELLA PW laser provided up to 46 J on target with a 1% level energy fluctuation and 1.3-μrad pointing stability. The spatial profile was measured and optimized by using a camera, wavefront sensor, and deformable mirror (ILAO system). The focus waist was measured to be r 0 = 53 μm and the fraction of energy within the circular area defined by the first minimum of the diffraction pattern (r = 67 μm) was 0.75. The temporal profile was controlled via the angle of incidence on a stretcher and a compressor, as well as an acousto-optic programmable dispersive. The temporal pulse shape was measured to be about 33 fs in full width at half maximum (WIZZLER and GRENOUILLE diagnostics). In order to accurately evaluate peak intensity, the energy-normalized peak fluence, and energy-normalized peak power were analyzed for the measured spatial and temporal mode profiles, and were found to be 15 kJ/(cm 2 J) with 6% fluctuation (standard deviation) and 25 TW/J with 5% fluctuation for 46-J on-target energy, respectively. This yielded a peak power of 1.2 PW and a peak intensity of 17×10 18 W/cm 2 with 8% fluctuation. A method to model the pulse shape for arbitrary compressor grating distance with high accuracy was developed. The pulse contrast above the amplified spontaneous emission pedestal was measured by SEQUOIA and found to be better than 10 9 . The first order spatiotemporal couplings (STCs) were measured with GRENOUILLE, and a simulation of the pulse's evolution at the vicinity of the target was presented. A maximum pulse front tilt angle of less than 7 mrad was achieved. The reduction of the peak power caused by the first order STCs was estimated to be less than 1%. Finally, the capabilities described in this paper are essential for generation of high quality electron beams.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

A Voxel-Based Approach to Explore Local Dose Differences Associated With Radiation-Induced Lung Damage

Purpose: To apply a voxel-based (VB) approach aimed at exploring local dose differences associated with late radiation-induced lung damage (RILD). Methods and Materials: An interinstitutional database of 98 patients who were Hodgkin lymphoma (HL) survivors treated with postchemotherapy supradiaphragmatic radiation therapy was analyzed in the study. Eighteen patients experienced late RILD, classified according to the Radiation Therapy Oncology Group scoring system. Each patient's computed tomographic (CT) scan was normalized to a single reference case anatomy (common coordinate system, CCS) through a log-diffeomorphic approach. The obtained deformation fields were used to map the dose of each patient into the CCS. The coregistration robustness and the dose mapping accuracy were evaluated by geometric and dose scores. Two different statistical mapping schemes for nonparametric multiple permutation inference on dose maps were applied, and the corresponding P<.05 significance lung subregions were generated. A receiver operating characteristic (ROC)-based test was performed on the mean dose extracted from each subregion. Results: The coregistration process resulted in a geometrically robust and accurate dose warping. A significantly higher dose was consistently delivered to RILD patients in voxel clusters near the peripheral medial-basal portion of the lungs. The area under the ROC curves (AUC) from the mean dose of the voxel clusters was higher than the corresponding AUC derived from the total lung mean dose. Conclusions: We implemented a framework including a robust registration process and a VB approach accounting for the multiple comparison problem in dose-response modeling, and applied it to a cohort of HL survivors to explore a local dose–RILD relationship in the lungs. Patients with RILD received a significantly greater dose in parenchymal regions where low doses (∼6 Gy) were delivered. Interestingly, the relation between differences in the high-dose range and RILD seems to lack a clear spatial signature.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries—PERSIANN-cGAN

In this paper, we present a state-of-the-art precipitation estimation framework which leverages advances in satellite remote sensing as well as Deep Learning (DL). The framework takes advantage of the improvements in spatial, spectral and temporal resolutions of the Advanced Baseline Imager (ABI) onboard the GOES-16 platform along with elevation information to improve the precipitation estimates. The procedure begins by first deriving a Rain/No Rain (R/NR) binary mask through classification of the pixels and then applying regression to estimate the amount of rainfall for rainy pixels. A Fully Convolutional Network is used as a regressor to predict precipitation estimates. The network is trained using the non-saturating conditional Generative Adversarial Network (cGAN) and Mean Squared Error (MSE) loss terms to generate results that better learn the complex distribution of precipitation in the observed data. Common verification metrics such as Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Bias, Correlation and MSE are used to evaluate the accuracy of both R/NR classification and real-valued precipitation estimates. Statistics and visualizations of the evaluation measures show improvements in the precipitation retrieval accuracy in the proposed framework compared to the baseline models trained using conventional MSE loss terms. This framework is proposed as an augmentation for PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network- Cloud Classification System) algorithm for estimating global precipitation.

42 ENGINEERING↗

DOE OSTI2022

Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data

Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. This data package includes one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Thermal Stratification Analysis for Sodium Fast Reactors

The sodium fast reactor (SFR) is the most mature reactor concept of all the generation-IV nuclear systems and is a promising reactor design that is currently under development by several organizations. The majority of sodium fast reactor designs utilize a pool type arrangement which incorporates the primary coolant pumps and intermediate heat exchangers within the sodium pool. These components typically protrude into the pool thus reducing the risk and severity of a loss of coolant accidents. To further ensure safe operation under even the most severe transients a more comprehensive understanding of key thermal hydraulic phenomena in this pool is desired. One of the key technology gaps identified for SFR safety is determining the extent and the effects of thermal stratification developing in the pool during postulated accident scenarios such as a protected or unprotected loss of flow incident. In an effort to address these issues, detailed flow models of transient stratification in the pool during an accident can be developed. However, to develop the calculation models, and ensure they can reproduce the underlying physics, highly spatially resolved data is needed. This data can be used in conjunction with advanced computational fluid dynamic calculations to aid in the development of simple reduced dimensional models for systems codes such as SAM and SAS4A/SASSYS-1.

Schneider, James↗

DOE OSTI2018

Thermal Stratification Analysis for Sodium Fast Reactors

The sodium fast reactor (SFR) is the most mature reactor concept of all the generation-IV nuclear systems and is a promising reactor design that is currently under development by several organizations. The majority of sodium fast reactor designs utilize a pool type arrangement which incorporates the primary coolant pumps and intermediate heat exchangers within the sodium pool. These components typically protrude into the pool thus reducing the risk and severity of a loss of coolant accidents. To further ensure safe operation under even the most severe transients a more comprehensive understanding of key thermal hydraulic phenomena in this pool is desired. One of the key technology gaps identified for SFR safety is determining the extent and the effects of thermal stratification developing in the pool during postulated accident scenarios such as a protected or unprotected loss of flow incident. In an effort to address these issues, detailed flow models of transient stratification in the pool during an accident can be developed. However, to develop the calculation models, and ensure they can reproduce the underlying physics, highly spatially resolved data is needed. This data can be used in conjunction with advanced computational fluid dynamic calculations to aid in the development of simple reduced dimensional models for systems codes such as SAM and SAS4A/SASSYS-1.

Schneider, James↗

DOE OSTI2016

A moment-convergence method for stochastic analysis of biochemical reaction networks

Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

A Wise census of young stellar objects in the Perseus OB2 association

We have performed a Wide-Field Infrared Survey Explorer based study to identify and characterize young stellar objects (YSOs) in the 12° × 12° Perseus OB2 association. A spectral energy distribution (SED) slope in the range of 3.4–12 μm and 5σ selection criteria were used to select our initial sample. Further manual inspection reduced our final catalog to 156 known and 119 YSO candidates. The spatial distribution of newly found YSOs all over the field shows an older generation of star formation in which most of its massive members have evolved into main-sequence stars. In contrast, the majority of younger members lie within the Perseus molecular cloud and currently active star-forming clusters such as NGC 1333 and IC 348. We also identified an additional 66 point sources that passed YSO selection criteria but are likely AGB stars. However, their spatial distribution suggests that they may contain a fraction of the YSOs. Comparing our results with the commonly used color–color selections, we found that while the color selection method fails in picking up bright but evolved weak disks, our SED fitting method can identify such sources, including transitional disks. In addition, we have less contamination with background sources such as galaxies, but at a price of losing fainter (J{sub mag}>12) YSOs. Finally, we employed a Bayesian Monte Carlo SED fitting method to determine the characteristics of each YSO candidate. Distribution of SED slopes and model-driven age and mass confirms separated YSO populations with three suggested age groups of younger than 1 Myr old, 1–5 Myr old, and older than 5 Myr, which agrees with the age of the Per OB2 association and currently star-forming sites within the cloud.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Reactive Transport Simulation of Fracture Channelization and Transmissivity Evolution

Underground fractures serve as flow conduits, and they may produce unwanted migration of water and other fluids in the subsurface. An example is the migration and leakage of greenhouse gases in the context of geologic carbon sequestration. This study has generated new understanding about how acids erode carbonate fracture surfaces and the positive feedback between reaction and flow. A two-dimensional reactive transport model was developed and used to investigate the extent to which geochemical factors influence fracture permeability and transmissivity evolution in carbonate rocks. The only mineral modeled as reactive is calcite, a fast-reacting mineral that is abundant in subsurface formations. The X-ray computed tomography dataset from a previous experimental study of fractured cores exposed to carbonic acid served as a testbed to benchmark the model simulation results. The model was able to capture not only erosion of fracture surfaces but also the specific phenomenon of channelization, which produces accelerating transmissivity increase. Results corroborated experimental findings that higher reactivity of the influent solution leads to strong channelization without substantial mineral dissolution. Simulations using mineral maps of calcite in a specimen of Amherstburg limestone demonstrated that mineral heterogeneity can either facilitate or suppress the development of flow channels depending on the spatial patterns of reactive mineral. In these cases, fracture transmissivity may increase rapidly, increase slowly, or stay constant, and for all these possibilities, the calcite mineral continues to dissolve. Collectively, these results illustrate that fluid chemistry and mineral spatial patterns need to be considered in predictions of reaction-induced fracture alteration and risks of fluid migration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

WE-DE-BRA-06: Evaluation of the Imaging Performance of a Novel Water-Equivalent EPID

Purpose: To evaluate the megavoltage imaging performance of a novel, water-equivalent electronic portal imaging device (EPID) developed for simultaneous imaging and dosimetry applications in radiotherapy. Methods: A novel EPID prototype based on active matrix flat panel imager technology has been developed by our group and previously reported to exhibit a water-equivalent dose response. It was constructed by replacing all components above the photodiode detector in a standard clinical EPID (including the copper plate and phosphor screen) with a 15 × 15 cm{sup 2} array of plastic scintillator fibers. Individual fibers measured 0.5 × 0.5 × 30 mm{sup 3}. Spatial resolution was evaluated experimentally relative to that of a standard EPID with the thin slit technique to measure the modulation transfer function (MTF) for 6 MV x-ray beams. Monte Carlo (MC) EPID models were used to benchmark simulated MTFs against the measurements. The zero spatial frequency detective quantum efficiency (DQE(0)) was simulated for both EPID configurations and a preliminary optimization of the prototype was performed by evaluating DQE(0) as a function of fiber length up to 50 mm. Results: The MC-simulated DQE(0) for the prototype EPID configuration was ∼7 times greater than that of the standard EPID. The prototype’s DQE(0) also increased approximately linearly with fiber length, from ∼1% at 5 mm length to ∼11% at 50 mm length. The standard EPID MTF was greater than the prototype EPID’s for all spatial frequencies, reflecting the trade off between x-ray detection efficiency and spatial resolution with thick scintillators. Conclusion: This study offers promising evidence that a water-equivalent EPID previously demonstrated for radiotherapy dosimetry may also be used for radiotherapy imaging applications. Future studies on optimising the detector design will be performed to develop a next-generation prototype that offers improved megavoltage imaging performance, with the aim to at least match that of current clinical EPIDs. Funding for this project was provided by an Australian Research Council Linkage Project grant (2015) between The University of Sydney, South Western Sydney Local Health District and Perkin-Elmer Pty Ltd.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

SPRUCE Microtopography of Experimental Plots Derived from Terrestrial Laser Scans Beginning in 2016

This dataset consists of maps and summaries of very high resolution (1 cm2) spatial data derived from terrestrial laser scans (TLS) characterizing the microtopography (hummocks and hollows) in 12 SPRUCE experimental plots from 2016-2018. The SPRUCE experiment is located in the S1-Bog of the Marcell Experimental Forest (MEF) near Grand Rapids, Minnesota. Additional data will be added through Summer 2021.The TLS sampling plan follows the SPRUCE experimental design, with scanning of the ten enclosed treatment plots with five temperature treatments (0, 2.25, 4.5, 6.75, and 9°C) with and without elevated CO2 (~900 ppm) and the two monitored ambient plots without enclosures. Enclosures are octagonal in shape and are 12.8 m in diameter (114.8 m2 in area), 8 m tall, with a belowground corral that penetrates through the peat to glacial material below, which averages 2.5 m deep across the site. In the spring of each year, four TLS scans were taken per plot/enclosure and registered together to produce a single point cloud for each plot (Figure 2A). Digital surface models (DSMs) were generated from the point clouds and clipped to the inside boundary of the boardwalk in each plot resulting in an approximately 9 x 9 m study area. . All other characterization data types were derived from plot DSMs (elevation), including: slope (Figure 3), concavity (Figure 4), index used for microform classification (Hollow Index) (Figure 6), and microforms (Figure 2C; hummocks and hollows) classified using three methodologies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

WE-H-206-00: Advances in Preclinical Imaging

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-H-206-01: Photoacoustic Tomography: Multiscale Imaging From Organelles to Patients by Ultrasonically Beating the Optical Diffusion Limit

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.

60 APPLIED LIFE SCIENCES↗