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DOE OSTI2021

IoT Intrusion Detection Taxonomy, Reference Architecture, and Analyses

This paper surveys the deep learning (DL) approaches for intrusion-detection systems (IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps, weaknesses, and a neutral reference architecture. A comparative study of IDSs is provided, with a review of anomaly-based IDSs on DL approaches, which include supervised, unsupervised, and hybrid methods. All techniques in these three categories have essentially been used in IoT environments. To date, only a few have been used in the anomaly-based IDS for IoT. For each of these anomaly-based IDSs, the implementation of the four categories of feature(s) extraction, classification, prediction, and regression were evaluated. We studied important performance metrics and benchmark detection rates, including the requisite efficiency of the various methods. Four machine learning algorithms were evaluated for classification purposes: Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and an Artificial Neural Network (ANN). Therefore, we compared each via the Receiver Operating Characteristic (ROC) curve. The study model exhibits promising outcomes for all classes of attacks. The scope of our analysis examines attacks targeting the IoT ecosystem using empirically based, simulation-generated datasets (namely the Bot-IoT and the IoTID20 datasets).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Technical and Imaging Outcomes from the UK Registry of Prostate Artery Embolization (UK-ROPE) Study: Focusing on Predictors of Clinical Success

Introduction: The UK Registry of Prostate Artery Embolization (UK-ROPE) was a prospective, multicentre study comparing PAE against surgical therapies for symptomatic benign prostatic hyperplasia (BPH). A wealth of data was collected supplementary to the main study outcomes which provide a snapshot of UK PAE practice. We aimed to interpret these data in the hope of providing insight into factors which affect clinical outcome and radiation dose. Methods: 216 patients (mean age 66, mean IPSS 21.3) undergoing PAE at 20 British centres from July 2014 to January 2016 were prospectively followed up to 12 months with retrospective analysis of the data. Technical outcome was evaluated based on procedural and fluoroscopy times, skin dose and dose area product (DAP). Clinical outcome was evaluated through collection of Qmax, IPSS reduction and prostate volume reduction. Multiple analysis of variance (MANOVA) was used to assess the significance of various patients and procedural factors on clinical outcome and patient dose. Results: Significant predictors of technical outcome which affected patient skin dose included severity of CTA-detected atheroma (p < 0.001), the practitioner (p < 0.001) and use of protective coil embolization (p = 0.019). Predictors of clinical outcome included initial prostate size (dichotomized into groups > 80 ml and = <80 ml, d = 1, p = 0.0138), embolic agent (spherical particles < 300 nm performed best, p = 0.01) and number of arteries embolized (IPSS reduction of 32.9% in unilateral PAE versus 54.4% for bilateral PAE, p = 0.026). Conclusion: We have identified several important factors which are associated with improved clinical outcome and increased patient dose which we hope will facilitate optimal patient selection and encourage improved embolization technique.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Hybrid PET/CT and PET/MRI imaging of vulnerable coronary plaque and myocardial scar tissue in acute myocardial infarction

Background: Following an acute coronary syndrome, combined CT and PET with {sup 18}F-NaF can identify coronary atherosclerotic plaques that have ruptured or eroded. However, the processes behind {sup 18}F-NaF uptake in vulnerable plaques remain unclear. Methods and Results: Ten patients with STEMI were scanned after {sup 18}F-NaF injection, for 75 minutes in a Siemens PET/MR scanner using delayed enhancement (LGE). They were then scanned in a Siemens PET/CT scanner for 10 minutes. Tissue-to-background ratio (TBR) was compared between the culprit lesion in the IRA and remote non-culprit lesions in an effort to independently validate prior studies. Additionally, we performed a proof-of-principle study comparing TBR in scar tissue and remote myocardium using LGE images and PET/MR or PET/CT data. From the 33 coronary lesions detected on PET/CT, TBRs for culprit lesions were higher than for non-culprit lesions (TBR = 2.11 ± 0.45 vs 1.46 ± 0.48; P < 0.001). Interestingly, the TBR measured on the PET/CT was higher for infarcted myocardium than for remote myocardium (TBR = 0.81 ± 0.10 vs 0.71 ± 0.05; P = 0.003). These results were confirmed using the PET/MR data (TBR = 0.81 ± 0.10 for scar, TBR = 0.71 ± 0.06 for healthy myocardium, P = 0.03). Conclusions: We confirmed the potential of {sup 18}F-NaF PET/CT imaging to detect vulnerable coronary lesions. Moreover, we demonstrated proof-of-principle that {sup 18}F-NaF concurrently detects myocardial scar tissue.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Energy production from waste: Evaluation of anaerobic digestion and bioelectrochemical systems based on energy efficiency and economic factors

Anaerobic digesters (AD) and bioelectrochemical systems (BES) are becoming increasingly popular technologies for the generation of renewable energy from wastes. Synergies between these technologies exist, however, configurations to couple them have been insufficiently investigated. This study compares the theoretical energy efficiencies of converting waste directly into electricity, using AD and BES alone and in various combinations. This study reviews the experimentally demonstrated energy efficiencies reported in the literature with comparisons to the maximum theoretical efficiencies, considering thermodynamic limits. Acetate is used as an ideal substrate for theoretical calculations, whereas complex wastes are used for extended analyses of practical efficiencies. In addition, to evaluate the economic potential of this technology, a brief case study was conducted using the Oak Ridge National Laboratory (ORNL) water resource recovery facility (WRRF). Sensitivity analysis was performed on several parameters in the economic model. The results of this study indicate the combined Anaerobic Digester/Microbial Electrolysis Cell (ADMEC) process may be the best path forward due to the high energy efficiency, combined with potential economic benefits, but is not at commercial readiness. We estimate energy efficiencies of 52.9% and 45.6% for the ADMEC process, using current state-of-the-technology, for converting food waste and sewage sludge to a CH 4 /H 2 mix, respectively. Finally, this study concludes with a discussion of new strategies to improve the energy efficiency of AD and BES processes.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Measuring the buried interphase between solid electrolytes and lithium metal using neutrons

Interfaces are the key to next-generation high-energy batteries including solid-state Li metal batteries. In solid-state batteries, the buried nature of solid–solid electrolyte–electrode interfaces makes studying them difficult. Neutrons have significant potential to non-destructively probe these buried solid–solid interfaces. This work presents a comparative study using both neutron depth profiling (NDP) and neutron reflectometry (NR) to study a model lithium metal–lithium phosphorus oxynitride (LiPON) solid electrolyte system. In the NDP data, no distinct interphase is observed at the interface. NR shows a difference between electrodeposited, and vapor deposited LiPON–Li interfaces but finds both are gradient interphases that are less than 30 nm thick. Additional simulations of the LiPON–Li 2 O–Li system demonstrate that NDP has an excellent resolution in the 50 nm–1 μm regime while NR has an ideal resolution from 0.1–200 nm with different sample requirements. Together NDP and NR can provide a complementary understanding of interfaces between Li metal and solid electrolytes across relevant length scales.

Westover, Andrew S. [Oak Ridge National Laboratory↗
DOE OSTI2024

Barium stars as tracers of s -process nucleosynthesis in AGB stars

Barium (Ba) stars help to verify asymptotic giant branch (AGB) star nucleosynthesis models since they experienced pollution from an AGB binary companion and thus their spectra carry the signatures of the slow neutron capture process (s process). For a large number (180) of Ba stars, we searched for AGB stellar models that match the observed abundance patterns. We aim to uncover any systematic deviations of the sample abundances from the predictions of the nucleosynthesis models. We employed three machine learning algorithms as classifiers: a Random Forest method, developed for this work, and the two classifiers used in our previous study. Compared to that work, we also expanded our observational sample with 11 Ba stars available in the supersolar metallicity range. We studied the statistical behaviour of the different s-process elements in the observational sample to investigate if the AGB models systematically under- or overpredict the abundances observed in the Ba stars and show the results in the form of violin plots of the residuals between spectroscopic abundances and model predictions. We inspected the correlations between the observed [Fe/H], the s-process elemental abundances, and the residuals. We employed the [Zr/Fe] and [Nb/Fe] abundances as a thermometer to constrain the operational temperature that rules the production of these elements in the sample stars, assuming a steady-state s process. We also investigated the mass distribution of the identified polluter AGB stars and the behaviour of the δ parameter, which describes the fraction of accreted AGB material relative to the Ba star envelope. We find a significant trend in the residuals that implies an underproduction of the elements just after the first s-process peak (Nb, Mo, and Ru) in the models relative to the observations. This may originate from a neutron-capture process (e.g. the intermediate neutron-capture process, i process) not yet included in the AGB models of metallicity from solar to roughly 1/5 solar, corresponding to the range of the Ba stars. Correlations are found between the residuals of these peculiar elements, suggesting a common origin for the deviations from the models. In addition, there is a weak metallicity dependence of the residuals of these elements. The s-process temperatures derived with the [Zr/Fe] – [Nb/Fe] thermometer have an unrealistic value for the majority of our stars. The most likely explanation is that at least a fraction of these elements are not produced in a steady-state s process, and instead may be due to processes not included in the AGB models. The mass distribution of the identified models confirms that our sample of Ba stars was polluted by low-mass AGB stars (< 4 M ⊙ ). Most of the matching AGB models require low accreted mass, but a few systems with high accreted mass are needed to explain the observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Exchange bias and magnetic properties induced by intrinsic structural distortion in CaMn{sub 3}O{sub 6} nanoribbons

Single-crystalline CaMn{sub 3}O{sub 6} nanoribbons have been synthesized by a molten-salt method. To explore the origin of the magnetism of nanosized antiferromagnetic (AFM) manganites, a comparative study has been conducted for CaMn{sub 3}O{sub 6} (CMO-1) and post-growth vacuum annealed (CMO-2) nanoribbons. A lattice expansion resulting from oxygen release during vacuum annealing is observed. Correspondingly, AFM ordering in CMO-2 is further suppressed, and ferromagnetism and spin-glass (SG)-like behavior are significantly enhanced, which are presumed attributable to the intrinsic structural distortions induced by oxygen vacancies. In this case, side and surface effects are not decisive factors. In addition, this study provided observations of the exchange bias effect in manganite nanoribbons with an AFM-SG-like-ferromagnetic (FM) structure, as compared with the typical AFM-core-FM-shell.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hydrodynamic description of D meson production in high-energy heavy-ion collisions *

The large values and constituent-quark-number scaling of the elliptic flow of low-p T D mesons imply that charm quarks, initially produced through hard processes, might be partially thermalized through strong interactions with quark-gluon plasma (QGP) in high-energy heavy-ion collisions. To quantify the degree of thermalization of low-p T charm quarks, we compare the D 0 meson spectra and elliptic flow from a hydrodynamic model to experimental data as well as transport model simulations. We use an effective charm chemical potential at the freeze-out temperature to account for the initial charm quark production from hard processes and assume that they are thermalized in the local comoving frame of the medium before freeze-out. D 0 mesons are sampled statistically from the freeze-out hyper-surface of the expanding QGP as described by the event-by-event (3+1)D viscous hydrodynamic model CLVisc. Both the hydrodynamic and transport models can describe the elliptic flow of D 0 mesons at P T < 3 GeV/c as measured in Au+Au collisions at $sqrts_{NN} = 200$ GeV. Though the experimental data on spectra are consistent with the hydrodynamic result at small p T ~ 1 GeV/c, they deviate from the hydrodynamic model at high transverse momentum, GeV/c. The diffusion and parton energy loss mechanisms in the transport model can describe the measured spectra reasonably well within the theoretical uncertainty. Finally, our comparative study indicates that charm quarks only approach local thermal equilibrium at small p T , even though they acquire sizable elliptic flow comparable to light-quark hadrons at both small and intermediate p T .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

BACKFLIP: Identification of Materials and Changes Upon Aging of Emerging Fluoropolymer-Free and Industry-Benchmark PV Backsheets

Extending lifetimes of photovoltaic (PV) modules and decreasing manufacturing and decommissioning costs are motivating research of novel PV module backsheet materials. Backsheet integrity is critical to the safety and performance of a PV module, however, the polymeric materials are often vulnerable to environmental degradation. The long-term durability of emerging polyolefin (PO) materials is being examined to inform regarding the possible replacement of laminated backsheets containing polyethylene terephthalate (PET) cores and fluoropolymer protective inner/outer layers. This study compares traditional PET-based backsheets with novel, co-extruded, and recyclable PO-based backsheets after being subjected to hygrometric and UV photolytic accelerated weathering. A large set of characterization methods will compare physical, chemical, structural, mechanical, and insulating properties of these backsheets and the resulting mini-module (MiMo) PV performances. The study of chemical composition, glass- and phase-transition temperatures, degree of crystallinity, and crystalline structure are described here.

mini-module↗
DOE OSTI2017

Machine Learning-Based Temperature Prediction for Runtime Thermal Management Across System Components

Elevated temperatures limit the peak performance of systems because of frequent interventions by thermal throttling. Non-uniform thermal states across system nodes also cause performance variation within seemingly equivalent nodes leading to significant degradation of overall performance. In this paper we present a framework for creating a lightweight thermal prediction system suitable for run-time management decisions. We pursue two avenues to explore optimized lightweight thermal predictors. First, we use feature selection algorithms to improve the performance of previously designed machine learning methods. Second, we develop alternative methods using neural network and linear regression-based methods to perform a comprehensive comparative study of prediction methods. We show that our optimized models achieve improved performance with better prediction accuracy and lower overhead as compared with the Gaussian process model proposed previously. Specifically we present a reduced version of the Gaussian process model, a neural network-based model, and a linear regression-based model. Using the optimization methods, we are able to reduce the average prediction errors in the Gaussian process from 4: 2 degrees C to 2: 9 degrees C. We also show that the newly developed models using neural network and Lasso linear regression have average prediction errors of 2: 9 degrees C and 3: 8 degrees C respectively. The prediction overheads are 0.22, 0.097, and 0.026 ms per prediction for reduced Gaussian process, neural network, and Lasso linear regression models, respectively, compared with 0.57 ms per prediction for the previous Gaussian process model. We have implemented our proposed thermal prediction models on a two-node system configuration to help identify the optimal task placement. The task placement identified by the models reduces the average system temperature by up to 11: 9 degrees C without any performance degradation. Furthermore, these models respectively achieve 75, 82.5, and 74.17 percent success rates in correctly pointing to those task placements with better thermal response, compared with 72.5 percent success for the original model in achieving the same objective. Lastly, we extended our analysis to a 16-node system and we were able to train models and execute them in real time to guide task migration and achieve on average 17 percent reduction in the overall system cooling power.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Differential timing of gene expression and recruitment in independent origins of CAM in the Agavoideae (Asparagaceae)

Crassulacean acid metabolism (CAM) photosynthesis has evolved repeatedly across the plant tree of life, however our understanding of the genetic convergence across independent origins remains hampered by the lack of comparative studies. Here, we explore gene expression profiles in eight species from the Agavoideae (Asparagaceae) encompassing three independent origins of CAM. Using comparative physiology and transcriptomics, we examined the variable modes of CAM in this subfamily and the changes in gene expression across time of day and between well watered and drought-stressed treatments. We further assessed gene expression and the molecular evolution of genes encoding phosphoenolpyruvate carboxylase (PPC), an enzyme required for primary carbon fixation in CAM. Most time-of-day expression profiles are largely conserved across all eight species and suggest that large perturbations to the central clock are not required for CAM evolution. By contrast, transcriptional response to drought is highly lineage specific. Yucca and Beschorneria have CAM-like expression of PPC2 , a copy of PPC that has never been shown to be recruited for CAM in angiosperms. Together the physiological and transcriptomic comparison of closely related C 3 and CAM species reveals similar gene expression profiles, with the notable exception of differential recruitment of carboxylase enzymes for CAM function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Casein from Bovine Milk as a Binder for Silicon Based Electrodes

Silicon is a promising anode material for lithium ion batteries due to the high theoretical capacity (∼3600mAh/g). However, silicon-based electrodes face rapid degradation due to the extensive volume variation (∼300%) during the lithiation/delithiation process. Binders used in the electrode fabrication play a crucial role for silicon electrodes since it can reduce the mechanical fracture during the cycling process. Recent investigations suggest that in addition to the importance of the mechanical properties of the binder, the chemical reactions between the binder and the surface of the silicon particles also contribute to stabilization. Further investigations suggest that functionalized small molecules can also modify the surface of silicon particles and stabilize cycling. An inexpensive, environmentally friendly alternative has been investigated as a binder for silicon electrodes. Casein is a milk protein found in bovine milk rich in amine groups and carboxylic acid groups which can form bonds with the silanol groups in silicon. A comparative study conducted between PVDF and Casein as binders have shown that when casein was used as binder, it shows better performance compared to PVDF. Surface morphology and solid electrolyte interphase (SEI) was analyzed using electron microscopy techniques and spectroscopic methods and the results will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Reduced peripheral activity leading to hepato‐preferential action of basal insulin peglispro compared with insulin glargine in patients with type 1 diabetes

Aims Basal insulin peglispro ( BIL ), a novel PEGylated basal insulin with a large hydrodynamic size, has a delayed absorption and reduced clearance that prolongs the duration of action. The current study compared the effects of BIL and insulin glargine ( GL ) on endogenous glucose production ( EGP ), glucose disposal rate ( GDR ) and lipolysis in patients with type 1 diabetes. Materials and Methods This was a randomized, open‐label, four‐period, crossover study. Patients received intravenous infusions of BIL and GL , each at two dose levels selected for partial and maximal suppression of EGP , during an 8 to 10 h euglycemic clamp procedure with d ‐[3‐ 3 H] glucose. Results Following correction for equivalent human insulin concentrations ( EHIC ), low‐dose GL infusion resulted in similar EGP at the end of the clamp compared to low‐dose BIL infusion ( GL / BIL ratio of 1.03) but a higher GDR ( GL / BIL ratio of 2.42), indicating similar hepatic activity but attenuated peripheral activity of BIL . Consistent with this, the EHIC ‐corrected GDR / EGP at the end of the clamp was 1.72‐fold greater for GL than BIL following low‐dose administration. At the lower dose of BIL and GL (concentrations in the therapeutic range), BIL produced less suppression of lipolysis compared with GL as indicated by free fatty acid and glycerol levels at the end of the clamp. Conclusions Compared with GL , BIL restored the hepato‐peripheral insulin action gradient seen in normal physiology via its peripherally restricted action on target tissues related to carbohydrate and lipid metabolism.

Mudaliar, S.↗
DOE OSTI2020

Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5

This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.

58 GEOSCIENCES↗
DOE OSTI2016

Dosimetric evaluation of total marrow irradiation using 2 different planning systems

This study compared 2 different treatment planning systems (TPSs) for quality and efficiency of total marrow irradiation (TMI) plans. The TPSs used in this study were VOxel-Less Optimization (VoLO) (Accuray Inc, Sunnyvale, CA) using helical dose delivery on a Tomotherapy Hi-Art treatment unit and Eclipse (Varian Medical Systems Inc, Palo Alto, CA) using volumetric modulated arc therapy (VMAT) dose delivery on a Varian iX treatment unit. A total dose of 1200 cGy was prescribed to cover 95% of the planning target volume (PTV). The plans were optimized and calculated based on a single CT data and structure set using the Alderson Rando phantom (The Phantom Laboratory, Salem, NY) and physician contoured target and organ at risk (OAR) volumes. The OARs were lungs, heart, liver, kidneys, brain, and small bowel. The plans were evaluated based on plan quality, time to optimize the plan and calculate the dose, and beam on time. The resulting mean and maximum doses to the PTV were 1268 and 1465 cGy for VoLO and 1284 and 1541 cGy for Eclipse, respectively. For 5 of 6 OAR structures the VoLO system achieved lower mean and D10 doses ranging from 22% to 52% and 3% to 44%, respectively. Total computational time including only optimization and dose calculation were 0.9 hours for VoLO and 3.8 hours for Eclipse. These times do not include user-dependent target delineation and field setup. Both planning systems are capable of creating high-quality plans for total marrow irradiation. The VoLO planning system was able to achieve more uniform dose distribution throughout the target volume and steeper dose fall off, resulting in superior OAR sparing. VoLO's graphics processing unit (GPU)–based optimization and dose calculation algorithm also allowed much faster creation of TMI plans.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Graphene as transparent and current spreading electrode in silicon solar cell

Fabricated bi-layer graphene (BLG) has been studied as transparent and current spreading electrode (TCSE) for silicon solar cell, using TCAD-Silvaco 2D simulation. We have carried out comparative study using both Ag grids and BLG as current spreading electrode (CSE) and TCSE, respectively. Our study reveals that BLG based solar cell shows better efficiency of 24.85% than Ag-based cell (21.44%), in all of the critical aspects, including generation rate, recombination rate, electric field, potential and quantum efficiency. Further BLG based cell exhibits pronounce rectifying behavior, low saturation current, and good turn-on voltage while studying in dark.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The buffering capacity of stems: genetic architecture of nonstructural carbohydrates in cultivated Asian rice, Oryza sativa

Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice ( Oryza sativa ) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associated with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. Furthermore, this study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species.

09 BIOMASS FUELS↗