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1. 2-km resolution oversampled NH3 data

Author(s):
Wang, Rui; Guo, Xuehui; Pan, Da; Kelly, James; Bash, Jesse; Sun, Kang; Paulot, Fabien; Clarisse, Lieven; Van Damme, Martin; Whitburn, Simon; Coheur, Pierre-François; Clerbaux, Cathy; Zondlo, Mark
Abstract:
Monthly, high resolution (~2 km) ammonia (NH3) column maps from the Infrared Atmospheric Sounding Interferometer (IASI) were developed across the contiguous United States and adjacent areas. Ammonia hotspots (95th percentile of the column distribution) were highly localized with a characteristic length scale of 12 km and median area of 152 km2. Five seasonality classes were identified with k-means++ clustering. The Midwest and eastern United States had a broad, spring maximum of NH3 (67% of hotspots in this cluster). The western United States, in contrast, showed a narrower mid-summer peak (32% of hotspots). IASI spatiotemporal clustering was consistent with those from the Ammonia Monitoring Network. CMAQ and GFDL-AM3 modeled NH3 columns have some success replicating the seasonal patterns but did not capture the regional differences. The high spatial-resolution monthly NH3 maps serve as a constraint for model simulations and as a guide for the placement of future, ground-based network sites.
Type:
Dataset
Issue Date:
December 2020

2. A dual-mechanism antibiotic kills Gram-negative bacteria and avoids drug resistance

Author(s):
Martin, James K; Sheehan, Joseph P; Bratton, Benjamin P; Moore, Gabriel M; Mateus, André; Li, Sophia Hsin-Jung; Kim, Hahn; Rabinowitz, Joshua D; Typas, Athanasios; Savitski, Mikhail M; Wilson, Maxwell Z; Gitai, Zemer
Abstract:
The rise of antibiotic resistance and declining discovery of new antibiotics have created a global health crisis. Of particular concern, no new antibiotic classes have been approved for treating Gram-negative pathogens in decades. Here, we characterize a compound, SCH-79797, that kills both Gram-negative and Gram-positive bacteria through a unique dual-targeting mechanism of action (MoA) with undetectably-low resistance frequencies. To characterize its MoA, we combined quantitative imaging, proteomic, genetic, metabolomic, and cell-based assays. This pipeline demonstrates that SCH-79797 has two independent cellular targets, folate metabolism and bacterial membrane integrity, and outperforms combination treatments in killing MRSA persisters. Building on the molecular core of SCH-79797, we developed a derivative, Irresistin-16, with increased potency and showed its efficacy against Neisseria gonorrheae in a mouse vaginal infection model. This promising antibiotic lead suggests that combining multiple MoAs onto a single chemical scaffold may be an underappreciated approach to targeting challenging bacterial pathogens.
Type:
Dataset
Issue Date:
20 May 2020

3. Analytic stability boundaries for compressional and global Alfven eigenmodes driven by fast ions. I. Interaction via ordinary and anomalous cyclotron resonances.

Author(s):
Lestz J.B., Gorelenkov N.N., Belova E.V., Tang S.X., Crocker N.A.
Abstract:
Conditions for net fast ion drive are derived for beam-driven, sub-cyclotron compressional (CAE) and global (GAE) Alfven eigenmodes, such as those routinely observed in spherical tokamaks such as NSTX(-U) and MAST. Both co- and counter-propagating CAEs and GAEs are investigated, driven by the ordinary and anomalous Doppler-shifted cyclotron resonance with fast ions. Whereas prior results were restricted to vanishingly narrow distributions in velocity space, broad parameter regimes are identified in this work which enable an analytic treatment for realistic fast ion distributions generated by neutral beam injection. The simple, approximate conditions derived in these regimes for beam distributions of realistic width compare well to the numerical evaluation of the full analytic expressions for fast ion drive. Moreover, previous results in the very narrow beam case are corrected and generalized to retain all terms in omega/omega_{ci} and k_{||}/kperp, which are often assumed to be small parameters but can significantly modify the conditions of drive and damping when they are non-negligible. Favorable agreement is demonstrated between the approximate stability criterion, simulation results, and a large database of NSTX observations of cntr-GAEs.
Type:
Dataset
Issue Date:
September 2019

4. Analytic stability boundaries for compressional and global Alfven eigenmodes driven by fast ions. II. Interaction via Landau resonance.

Author(s):
Lestz, J.B.; Gorelenkov, N.N.; Belova, E.V.; Tang, S.X.; Crocker, N.A.
Abstract:
Conditions for net fast ion drive are derived for beam-driven, co-propagating, sub-cyclotron compressional (CAE) and global (GAE) Alfven eigenmodes driven by the Landau resonance with super-Alfvenic fast ions. Approximations applicable to realistic neutral beam distributions and mode characteristics observed in spherical tokamaks enable the derivation of marginal stability conditions for these modes. Such conditions successfully reproduce the stability boundaries found from numerical integration of the exact expression for local fast ion drive/damping. Coupling between the CAE and GAE branches of the dispersion due to finite \omega/\omega_{ci} and k_\parallel/k_\perp is retained and found to be responsible for the existence of the GAE instability via this resonance. Encouraging agreement is demonstrated between the approximate stability criterion, simulation results, and a database of NSTX observations of co-CAEs.
Type:
Dataset
Issue Date:
January 2020

5. Chinese overseas development financing of electric power generation: A comparative analysis

Author(s):
Chen, Xu; Gallagher, Kevin P.; Mauzerall, Denise L.
Abstract:
Global power generation must rapidly decarbonize by mid-century to meet the goal of stabilizing global warming below 2 degree Celsius. To meet this objective, multilateral development banks (MDBs) have gradually reduced fossil fuel and increased renewable energy financing. Meanwhile, globally active national development finance institutions (DFIs) from Japan and South Korea have continued to finance overseas coal plants. Less is known about the increasingly active Chinese DFIs. Here we construct a new dataset of China’s policy banks’ overseas power generation financing and compare their technology choices and impact on generation capacity with MDBs and Japanese and South Korean DFIs. We find Chinese DFI power financing since 2000 has dramatically increased, surpassing other East Asian national DFIs and the major MDBs’ collective public sector power financing in 2013. As most Chinese DFI financing is currently in coal, decarbonization of their power investments will be critical in reducing future carbon emissions from recipient countries.
Type:
Dataset
Issue Date:
23 October 2020

6. Data for food consumption strategies in China

Author(s):
Guo, Yixin; Mauzerall, Denise; He, Pan
Abstract:
This dataset provides the data generated during the project analyzing ‘Food Consumption Strategies for Addressing Air Pollution, Climate Change, Water Use, and Public Health in China’. It includes the code for generating the alternative dietary scenarios, for analyzing the health impacts of alternative diets, and for visualization of results.
Type:
Dataset
Issue Date:
31 October 2020

7. Data from "Manifestations of metastable criticality in glassy water-like models detected by large-scale structural properties"

Author(s):
Gartner III, Thomas E.; Torquato, Salvatore; Car, Roberto; Debenedetti, Pablo G.
Abstract:
This dataset contains all data related to the publication "Manifestations of metastable criticality in glassy water-like models detected by large-scale structural properties" by Gartner et al., in preparation 2020. In this work, we used molecular dynamics simulations to explore the relationship between water's polyamorphism (multiple amorphous solid states) and its hypothesized liquid-liquid transition. Using the TIP4P/2005 molecular model of water, we found a surprising signature of water's liquid-liquid critical point in the long-range structure of water's amorphous solid states formed by isobaric cooling at different pressures. This structural signature was absent in two other systems that lack a critical point. This dataset contains molecular dynamics simulation trajectories, as well as processed data, analysis codes, and image files used in the publication.
Type:
Dataset
Issue Date:
3 December 2020

8. Data from "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water"

Author(s):
Gartner, Thomas III; Zhang, Linfeng; Piaggi, Pablo; Car, Roberto; Panagiotopoulos, Athanassios; Debenedetti, Pablo
Abstract:
This dataset contains all data related to the publication "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water", by Gartner et al., 2020. In this work, we used neural networks to generate a computational model for water using high-accuracy quantum chemistry calculations. Then, we used advanced molecular simulations to demonstrate evidence that suggests this model exhibits a liquid-liquid transition, a phenomenon that can explain many of water's anomalous properties. This dataset contains links to all software used, all data generated as part of this work, as well as scripts to generate and analyze all data and generate the plots reported in the publication.
Type:
Dataset
Issue Date:
July 2020

9. Data from a flume experiment of passive scalar diffusion within vegetation canopies using laser-induced fluorescence

Author(s):
Ghannam, Khaled; Poggi, Davide; Katul, Gabriel; Bou-Zeid, Elie
Abstract:
This dataset is a sequence of laser-induced fluorescence images of a dye injected in a channel flow with canopy-like stainless steel rods simulating a vegetation canopy stand. The data is acquired close to the channel bottom at z/h=0.2, where z is the height referenced to the channel bed and h is the canopy height. The dataset provides spatial distribution of scalar concentration in a plane parallel to the channel bed. The data has been used (but the data itself has not been published or available to the public) in previous work. The references are: Ghannam, K., Poggi, D., Porporato, A., & Katul, G. (2015). The spatio-temporal statistical structure and ergodic behaviour of scalar turbulence within a rod canopy. Boundary-Layer Meteorology,157(3), 447–460. Ghannam, K, Poggi, D., Bou-Zeid, E., Katul, G. (2020). Inverse cascade evidenced by information entropy of passive scalars in submerged canopy flows. Geophysical Research Letters (accepted).
Type:
Dataset
Issue Date:
22 April 2020

10. Dataset for 'Auditory Activity is Diverse and Widespread Throughout the Central Brain of Drosophila'

Author(s):
Pacheco, Diego A; Thiberge, Stephan; Pnevmatikakis, Eftychios; Murthy, Mala
Abstract:
Sensory pathways are typically studied starting at receptor neurons and following postsynaptic neurons into the brain. However, this leads to a bias in analysis of activity towards the earliest layers of processing. Here, we present new methods for volumetric neural imaging with precise across-brain registration, to characterize auditory activity throughout the entire central brain of Drosophila and make comparisons across trials, individuals, and sexes. We discover that auditory activity is present in most central brain regions and in neurons responsive to other modalities. Auditory responses are temporally diverse, but the majority of activity is tuned to courtship song features. Auditory responses are stereotyped across trials and animals in early mechanosensory regions, becoming more variable at higher layers of the putative pathway, and this variability is largely independent of spontaneous movements. This study highlights the power of using an unbiased, brain-wide approach for mapping the functional organization of sensory activity.
Type:
Dataset
Issue Date:
October 2020

11. Dataset for China's foreign direct investment in the global power sector

Author(s):
Li, Zhongshu; Gallagher, Kevin P.; Mauzerall, Denise L.
Abstract:
The dataset include a list of power projects outside of China that receive Chinese foreign direct investment from 2000 to 2018. Detailed information including project capacity, location, share of Chinese ownership, type of power generating technologies are collected for each power project.
Type:
Dataset
Issue Date:
January 2020

12. Deep Potential training data for crystalline and disordered TiO2 phases

Author(s):
Calegari Andrade, Marcos; Selloni, Annabella
Abstract:
Data set used to train a Deep Potential (DP) model for crystalline and disordered TiO2 phases. Training data contain atomic forces, potential energy, atomic coordinates and cell tensor. Energy and forces were evaluated with the density functional SCAN, as implemented in Quantum-ESPRESSO. Atomic configurations of crystalline systems were generated by random perturbation of atomic positions (0-0.3 A) and cell tensor (1-10%). Amorphous TiO2 was explored by DP molecular dynamics (DPMD) at temperatures in the range 300−2500 K and pressure in the range 0−81 GPa.
Type:
Dataset
Issue Date:
9 October 2020

13. Deep Potential training data for subcritical and supercritical water

Author(s):
Calegari Andrade, Marcos; Ko, Hsin-Yu; Car, Roberto
Abstract:
Data set used to train a Deep Potential (DP) model for subcritical and supercritical water. Training data contain atomic forces, potential energy, atomic coordinates and cell tensor. Energy and forces were evaluated with the density functional SCAN. Atomic configurations were extracted from DP molecular dynamics at P = 250 bar and T = 553, 623, 663, 733 and 823 K. Input files used to train the DP model are also provided.
Type:
Dataset
Issue Date:
19 August 2020

14. Deep convolutional neural networks for multi-scale time-series classification and application to disruption prediction in fusion devices

Author(s):
Churchill, R.M; the DIII-D team
Abstract:
The multi-scale, mutli-physics nature of fusion plasmas makes predicting plasma events challenging. Recent advances in deep convolutional neural network architectures (CNN) utilizing dilated convolutions enable accurate predictions on sequences which have long-range, multi-scale characteristics, such as the time-series generated by diagnostic instruments observing fusion plasmas. Here we apply this neural network architecture to the popular problem of disruption prediction in fusion tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. ECEi measures a fundamental plasma quantity (electron temperature) with high temporal resolution over the entire plasma discharge, making it sensitive to a number of potential pre-disruptions markers with different temporal and spatial scales. Promising, initial disruption prediction results are obtained training a deep CNN with large receptive field ({$\sim$}30k), achieving an $F_1$-score of {$\sim$}91\% on individual time-slices using only the ECEi data.
Type:
Dataset
Issue Date:
October 2019

15. Distinct cytoskeletal proteins define zones of enhanced cell wall synthesis in Helicobacter pylori

Author(s):
Taylor, Jenny A.; Bratton, Benjamin P.; Sichel, Sophie R.; Blair, Kris M.; Jacobs, Holly M.; DeMeester, Kristen E.; Kuru, Erkin; Gray, Joe; Biboy, Jacob; VanNieuwenhze, Michael S.; Vollmer, Waldemar; Grimes, Catherine L.; Shaevitz, Joshua W.; Salama, Nina R.
Abstract:
Helical cell shape is necessary for efficient stomach colonization by Helicobacter pylori, but the molecular mechanisms for generating helical shape remain unclear. We show that the helical centerline pitch and radius of wild-type H. pylori cells dictate surface curvatures of considerably higher positive and negative Gaussian curvatures than those present in straight- or curved-rod bacteria. Quantitative 3D microscopy analysis of short pulses with either N-acetylmuramic acid or D-alanine metabolic probes showed that cell wall growth is enhanced at both sidewall curvature extremes. Immunofluorescence revealed MreB is most abundant at negative Gaussian curvature, while the bactofilin CcmA is most abundant at positive Gaussian curvature. Strains expressing CcmA variants with altered polymerization properties lose helical shape and associated positive Gaussian curvatures. We thus propose a model where CcmA and MreB promote PG synthesis at positive and negative Gaussian curvatures, respectively, and that this patterning is one mechanism necessary for maintaining helical shape.
Type:
Dataset and Image
Issue Date:
April 2019

16. Enhanced Pedestal H-mode at low edge ion collisionality on NSTX

Author(s):
Battaglia, D.J.; Guttenfelder, W.; Bell, R.E.; Diallo, A.; Ferraro, N.;, Fredrickson, E.; Gerhardt, S.P.; Kaye, S.M.; Maingi, R.; Smith, D.R.
Abstract:
The Enhanced Pedestal (EP) H-mode regime is an attractive wide-pedestal ELM-free high-betap scenario for NSTX-U and next-step devices as it achieves enhanced energy confinement (H98y,2 > 1.5), large normalized pressure (betaN > 5) and significant bootstrap fraction (f_BS > 0.6) at I_p/B_T = 2 MA/T. This regime is realized when the edge ion collisionality becomes sufficiently small that a positive feedback interaction occurs between a reduction in the ion neoclassical energy transport and an increase in the particle transport from pressure-driven edge instabilities. EP H-mode was most often observed as a transition following a large ELM in conditions with low edge neutral recycling. It is hypothesized that the onset of pressure-driven instabilities prior to the full recovery of the neutral density leads to a temporary period with elevated ion temperature gradient that triggers the transition to EP H-mode. Linear CGYRO and M3D-C1 calculations are compared to beam emission spectroscopy (BES) and magnetic spectroscopy in order to describe the evolution of the edge particle transport mechanisms during the ELM recovery and the saturated EP H-mode state. The observations are consistent with the hypothesis that the onset of pressure-driven edge instabilities, such as the KBM and kink-peeling, can be responsible for the increased particle transport in EP H-mode.
Type:
Dataset
Issue Date:
June 2020

17. Femtosecond X-ray Diffraction of Laser-shocked Forsterite (Mg2SiO4) to 122 GPa

Author(s):
Kim, Donghoon; Tracy, Sally J.; Smith, Raymond F.; Gleason, Arianna E.; Bolme, Cindy A.; Prakapenka, Vitali B.; Appel, Karen; Speziable, Sergio; Wicks, June K.; Berryman, Eleanor J.; Han, Sirus K.; Schoelmerich, Markus O.; Lee, Hae Ja; Nagler, Bob; Cunningham, Eric F.; Akin, Minta C.; Asimow, Paul D.; Eggert, Jon H.; Duffy, Thomas S.
Abstract:
The behavior of forsterite, Mg2SiO4, under dynamic compression is of fundamental importance for understanding its phase transformations and high-pressure behavior. Here, we have carried out an in situ X-ray diffraction study of laser-shocked poly- and single-crystal forsterite (a-, b-, and c- orientations) from 19 to 122 GPa using the Matter in Extreme Conditions end-station of the Linac Coherent Light Source. Under laser-based shock loading, forsterite does not transform to the high-pressure equilibrium assemblage of MgSiO3 bridgmanite and MgO periclase, as was suggested previously. Instead, we observe forsterite and forsterite III, a metastable polymorph of Mg2SiO4, coexisting in a mixed-phase region from 33 to 75 GPa for both polycrystalline and single-crystal samples. Densities inferred from X-ray diffraction data are consistent with earlier gas-gun shock data. At higher stress, the behavior observed is sample-dependent. Polycrystalline samples undergo amorphization above 79 GPa. For [010]- and [001]-oriented crystals, a mixture of crystalline and amorphous material is observed to 108 GPa, whereas the [100]-oriented crystal adopts an unknown crystal structure at 122 GPa. The Q values of the first two sharp diffraction peaks of amorphous Mg2SiO4 show a similar trend with compression as those observed for MgSiO3 glass in both recent static and laser-compression experiments. Upon release to ambient pressure, all samples retain or revert to forsterite with evidence for amorphous material also present in some cases. This study demonstrates the utility of femtosecond free-electron laser X-ray sources for probing the time evolution of high-pressure silicates through the nanosecond-scale events of shock compression and release.
Type:
Dataset
Issue Date:
November 2020

18. Fluorescence Reconstruction Microscopy Data: Keratinocyte (10x) Phase to Nuclei (DAPI)

Author(s):
LaChance, Julienne; Cohen, Daniel
Abstract:
The data provided in this DataSpace consists of sample training data to be used for Fluorescence Reconstruction Microscopy (FRM) testing. We provide a subset of the keratinocyte (10x magnification) dataset used in our paper, in which interested parties may find more complete information about our data collection methods. Matched pairs of phase contrast and fluorescent images are given. The nuclei were stained using Hoechst 33342 and imaged using a standard DAPI filter set.
Type:
Dataset
Issue Date:
2 March 2020

19. Fluorescence Reconstruction Microscopy Data: MDCK (20x) DIC to Nuclei (DAPI) and E-Cadherin (RFP)

Author(s):
LaChance, Julienne; Cohen, Daniel
Abstract:
The data provided in this DataSpace consists of sample training data to be used for Fluorescence Reconstruction Microscopy (FRM) testing. We provide a subset of the MDCK (20x magnification) dataset used in our paper, in which interested parties may find more complete information about our data collection methods. Matched pairs of DIC and fluorescent images are given. The cells stably expressed E-cadherin:RFP which enabled imaging of junctional fluorescence, while the nuclei were stained using Hoechst 33342 and imaged using a standard DAPI filter set.
Type:
Dataset
Issue Date:
24 February 2020

20. Fluorescence Reconstruction Microscopy: Complete Testing Dataset

Author(s):
LaChance, Julienne; Cohen, Daniel
Abstract:
We provide all the test data and corresponding predictions for our paper, “Practical Fluorescence Reconstruction Microscopy for High-Content Imaging”. Please refer to the Methods section in this paper for experimental details. For each experimental condition, we provide the input transmitted-light images (either phase contrast or DIC), the ground truth fluorescence images, and the output predicted fluorescence images which should reconstruct the ground truth fluorescence images.
Type:
Dataset
Issue Date:
April 2020

21. Gyrokinetic understanding of the edge pedestal transport driven by resonant magnetic perturbations in a realistic divertor geometry

Author(s):
Hager, R.; Chang, C. S.; Ferraro, N. M.; Nazikian R.
Abstract:
Self-consistent simulations of neoclassical and electrostatic turbulent transport in a DIII-D H-mode edge plasma under resonant magnetic perturbations (RMPs) have been performed using the global total-f gyrokinetic particle-in-cell code XGC, in order to study density-pump out and electron heat confinement.The RMP field is imported from the extended magneto-hydrodynamics (MHD) code M3D-C1, taking into account the linear two-fluid plasma response.With both neoclassical and turbulence physics considered together, the XGC simulation reproduces two key features of experimentally observed edge transport under RMPs: increased radial particle transport in the pedestal region that is sufficient to account for the experimental pump-out rate, and suppression of the electron heat flux in the steepest part of the edge pedestal.In the simulation, the density fluctuation amplitude of modes moving in the electron diamagnetic direction increases due to interaction with RMPs in the pedestal shoulder and outward, while the electron temperature fluctuation amplitude decreases.
Type:
Dataset
Issue Date:
June 2020

22. MHD-blob correlations in NSTX

Author(s):
Zweben SJ; Fredrickson ED; Myra JR; Podesta M; Scotti F
Abstract:
This paper describes a study of the cross-correlations between edge fluctuations as seen in the gas puff imaging (GPI) diagnostic and low frequency coherent magnetic fluctuations (MHD) in H-mode plasmas in NSTX. The main new result was that large blobs in the SOL were significantly correlated with MHD activity the 3-6 kHz range in 21 of the 223 shots examined. There were also many other shots in which fluctuations in the GPI signal level and its peak radius Rpeak were correlated with MHD activity, but without any significant correlation of the MHD with large blobs. The structure and motion of the MHD is compared with that of the correlated blobs, and some possible theoretical mechanisms for the MHD-blob correlation are discussed.
Type:
Dataset
Issue Date:
May 2020

23. Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX

Author(s):
Woods, B. J. Q.; Duarte, V. N.; Fredrickson, E. D.; Gorelenkov, N. N.; Podestà, M.; Vann, R. G. L.
Abstract:
Abrupt large events in the Alfvenic and sub-Alfvenic frequency bands in tokamaks are typically correlated with increased fast-ion loss. Here, machine learning is used to speed up the laborious process of characterizing the behavior of magnetic perturbations from corresponding frequency spectrograms that are typically identified by humans. The analysis allows for comparison between different mode character (such as quiescent, fixed frequency, and chirping, avalanching) and plasma parameters obtained from the TRANSP code, such as the ratio of the neutral beam injection (NBI) velocity and the Alfven velocity (v_inj./v_A), the q-profile, and the ratio of the neutral beam beta and the total plasma beta (beta_beam,i / beta). In agreement with the previous work by Fredrickson et al., we find a correlation between beta_beam,i and mode character. In addition, previously unknown correlations are found between moments of the spectrograms and mode character. Character transition from quiescent to nonquiescent behavior for magnetic fluctuations in the 50200-kHz frequency band is observed along the boundary v_phi ~ (1/4)(v_inj. - 3v_A), where v_phi is the rotation velocity.
Type:
Dataset
Issue Date:
December 2019

25. March Mathness: Effects of basketball on the brain

Author(s):
Antony, James; McDougle, Sam
Abstract:
Surprise signals a discrepancy between past and current beliefs. It is theorized to be linked to affective experiences, the creation of particularly resilient memories, and segmentation of the flow of experience into discrete perceived events. However, the ability to precisely measure naturalistic surprise has remained elusive. We used advanced basketball analytics to derive a quantitative measure of surprise and characterized its behavioral, physiological, and neural correlates in human subjects observing basketball games. We found that surprise was associated with segmentation of ongoing experiences, as reflected by subjectively perceived event boundaries and shifts in neocortical patterns underlying belief states. Interestingly, these effects differed by whether surprising moments contradicted or bolstered current predominant beliefs. Surprise also positively correlated with pupil dilation, activation in subcortical regions associated with dopamine, game enjoyment, and long-term memory. These investigations support key predictions from event segmentation theory and extend theoretical conceptualizations of surprise to real-world contexts.
Type:
Dataset
Issue Date:
2020

26. Methane Emissions from Natural Gas Vehicles in China

Author(s):
Pan, Da; Tao, Lei; Golston, Levi; Miller, David; Zhu, Tong; Qin, Yue; Zhang, Yan; Mauzerall, Denise
Abstract:
Natural gas vehicles (NGVs) have been promoted in China to mitigate air pollution, yet our measurements and analyses show that NGV growth in China may have significant negative impacts on climate change. We conducted real-world vehicle emission measurements in China and found high methane emissions from heavy-duty NGVs (90% higher than current emission limits). These emissions have been ignored in previous emission estimates, leading to biased results. Applying our observations to life-cycle analyses, we found that switching to NGVs from conventional vehicles in China has led to a net increase in greenhouse gas (GHG) emissions since 2000. With scenario analyses, we also show that the next decade will be critical for China to reverse the trend with the upcoming China VI standard for heavy-duty vehicles. Implementing and enforcing the China VI standard is challenging, and the method demonstrated here can provide critical information regarding the fleet-level CH4 emissions from NGVs.
Type:
Dataset
Issue Date:
2020

27. Modeling of resistive plasma response in toroidal geometry using an asymptotic matching approach

Author(s):
Z. R. Wang; A. H. Glasser; D. Brennan; Y. Q. Liu; J-K. Park
Abstract:
The method of solving linear resistive plasma response, based on the asymptotic matching approach, is developed for full toroidal tokamaks by upgrading the Resistive DCON code [A.H. Glasser, Z.R. Wang and J.-K. Park, Physics of Plasmas, \textbf{23}, 112506 (2016)]. The derived matching matrix, asymptotically matching the outer and inner regions, indicates that the applied three dimension (3-D) magnetic perturbations contribute additional small solutions at each resonant surface due to the toroidal coupling of poloidal modes. In contrast, the resonant harmonic only affects the corresponding resonant surface in the cylindrical plasma. Since the solution of ideal outer region is critical to the asymptotic matching and is challenging to be solved in the toroidal geometry due to the singular power series solution at the resonant surfaces, systematic verification of the outer region $\Delta^\prime$ matrix is made by reproducing the well known analytical $\Delta^{\prime}$ result in [H.P. Furth, P.H. Rutherford and H. Selberg, The Physics of Fluids, \textbf{16}, 1054-1063 (1073)] as well as by making a quantitative benchmark with the PEST3 code [A. Pletzer and R.L. Dewar, J. Plasma Physics, \textbf{45}, 427-451 (1991)]. Finally, the reconstructed numerical solution of resistive plasma response from the toroidal matching matrix is presented. Comparing with the ideal plasma response, the global structure of the response can be affected by the small finite island at the resonant surfaces.
Type:
Dataset
Issue Date:
October 2020

28. Shakespeare and Company Project Dataset: Lending Library Books

Author(s):
Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Green, Elspeth; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Mahoney, Cate; McCarthy, Jesse D.; Naydan, Mary; Ruehl, Isabel; Thode, Sylvie; VanSant, Camey; Wulfman, Clifford E.
Abstract:
This dataset includes information about approximately 6,000 books and other items with bibliographic data as well as summary information about when the item circulated in the Shakespeare and Company lending library and the number of times an item was borrowed or purchased.
Type:
Dataset
Issue Date:
July 2020

29. Shakespeare and Company Project Dataset: Lending Library Events

Author(s):
Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Green, Elspeth; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Mahoney, Cate; McCarthy, Jesse D.; Naydan, Mary; Ruehl, Isabel; Thode, Sylvie; VanSant, Camey; Wulfman, Clifford E.
Abstract:
The events dataset includes information about approximately 33,700 lending library events including membership activities such as subscriptions, renewals and reimbursements and book-related activities such as borrowing and purchasing. For events related to lending library cards that are available as digital surrogates, IIIF links are provided.
Type:
Dataset
Issue Date:
July 2020

30. Shakespeare and Company Project Dataset: Lending Library Members

Author(s):
Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Green, Elspeth; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Mahoney, Cate; McCarthy, Jesse D.; Naydan, Mary; Ruehl, Isabel; Thode, Sylvie; VanSant, Camey; Wulfman, Clifford E.
Abstract:
The Shakespeare and Company Project: Lending Library Members dataset includes information about approximately 5,700 members of Sylvia Beach's Shakespeare and Company lending library.
Type:
Dataset
Issue Date:
July 2020

31. Shakespeare and Company Project Dataset: Lending Library Members, Books, Events

Author(s):
Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Green, Elspeth; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Mahoney, Cate; McCarthy, Jesse D.; Naydan, Mary; Ruehl, Isabel; Thode, Sylvie; VanSant, Camey; Wulfman, Clifford E.
Abstract:
The Shakespeare and Company Project makes three datasets available to download in CSV and JSON formats. The datasets provide information about lending library members; the books that circulated in the lending library; and lending library events, including borrows, purchases, memberships, and renewals. The datasets may be used individually or in combination site URLs are consistent identifiers across all three. The DOIs for each dataset are as follows: Members (https://doi.org/10.34770/ht30-g395); Books (https://doi.org/10.34770/g467-3w07); Events (https://doi.org/10.34770/2r93-0t85).
Type:
Dataset
Issue Date:
July 2020

32. Simulating pitch angle scattering using an explicitly solvable energy-conserving algorithm

Author(s):
Zhang, Xin; Fu, Yichen; Qin, Hong
Abstract:
Particle distribution functions evolving under the Lorentz operator can be simulated with the Langevin equation for pitch angle scattering. This approach is frequently used in particle based Monte-Carlo simulations of plasma collisions, among others. However, most numerical treatments do not guarantee energy conservation, which may lead to unphysical artifacts such as numerical heating and spectra distortions. We present a novel structure-preserving numerical algorithm for the Langevin equation for pitch angle scattering. Similar to the well-known Boris algorithm, the proposed numerical scheme takes advantage of the structure-preserving properties of the Cayley transform when calculating the velocity-space rotations. The resulting algorithm is explicitly solvable, while preserving the norm of velocities down to machine precision. We demonstrate that the method has the same order of numerical convergence as the traditional stochastic Euler-Maruyama method.
Type:
Dataset
Issue Date:
September 2020

33. Solitary zonal structures in subcritical drift waves: a minimum model

Author(s):
Yao Zhou; Hongxuan Zhu; I. Y. Dodin
Abstract:
{\rtf1\ansi\ansicpg1252\cocoartf1561\cocoasubrtf610{\fonttbl\f0\fswiss\fcharset0 Helvetica;}{\colortbl;\red255\green255\blue255;\red0\green0\blue0;}{\*\expandedcolortbl;;\cssrgb\c0\c0\c0;}\margl1440\margr1440\vieww10800\viewh8400\viewkind0\pard\tx887\tx1775\tx2662\tx3550\tx4438\tx5325\tx6213\tx7101\tx7988\tx8876\tx9764\tx10651\tx11539\tx12427\tx13314\tx14202\tx15090\tx15977\tx16865\tx17753\tx18640\tx19528\tx20416\tx21303\tx22191\tx23079\tx23966\tx24854\tx25742\tx26629\tx27517\tx28405\tx29292\tx30180\tx31067\tx31955\tx32843\tx33730\tx34618\tx35506\tx36393\tx37281\tx38169\tx39056\tx39944\tx40832\tx41719\tx42607\tx43495\tx44382\tx45270\tx46158\tx47045\tx47933\tx48821\tx49708\tx50596\tx51484\tx52371\tx53259\tx54147\tx55034\tx55922\tx56810\tx57697\tx58585\tx59472\tx60360\tx61248\tx62135\tx63023\tx63911\tx64798\tx65686\tx66574\tx67461\tx68349\tx69237\tx70124\tx71012\tx71900\tx72787\tx73675\tx74563\tx75450\tx76338\tx77226\tx78113\tx79001\tx79889\tx80776\tx81664\tx82552\tx83439\tx84327\tx85215\tx86102\tx86990\tx87877\tx88765\slleading20\pardirnatural\partightenfactor0\f0\fs38 \cf2 Solitary zonal structures have recently been identified in gyrokinetic simulations of subcritical drift-wave (DW) turbulence with background shear flows. However, the nature of these structures has not been fully understood yet. Here, we show that similar structures can be obtained within a reduced model, which complements the modified Hasegawa\'97Mima equation with a generic primary instability and a background shear flow. We also find that these structures can be qualitatively reproduced in the modified Hasegawa\'97Wakatani equation, which subsumes the reduced model as a limit. In particular, we illustrate that in both cases, the solitary zonal structures approximately satisfy the same \'93equation of state\'94, which is a local relation connecting the DW envelope with the zonal-flow velocity. Due to this generality, our reduced model can be considered as a minimum model for solitary zonal structures in subcritical DWs. }
Type:
Dataset
Issue Date:
March 2020

35. Statistical properties of magnetic structures and energy dissipation during turbulent reconnection in the Earth's magnetotail

Author(s):
Bergstedt, K.; Ji, H.; Jara-Almonte, J.; Yoo, J.; Ergun, R. E.; Chen, L.-J.
Abstract:
We present the first statistical study of magnetic structures and associated energy dissipation observed during a single period of turbulent magnetic reconnection, by using the in situ measurements of the Magnetospheric Multiscale mission in the Earth's magnetotail on 26 July 2017. The structures are selected by identifying a bipolar signature in the magnetic field and categorized as plasmoids or current sheets via an automated algorithm which examines current density and plasma flow. The size of the plasmoids forms a decaying exponential distribution ranging from subelectron up to ion scales. The presence of substantial number of current sheets is consistent with a physical picture of dynamic production and merging of plasmoids during turbulent reconnection. The magnetic structures are locations of significant energy dissipation via electric field parallel to the local magnetic field, while dissipation via perpendicular electric field dominates outside of the structures. Significant energy also returns from particles to fields.
Type:
Dataset
Issue Date:
14 September 2020

37. The Molino Suite of Galaxy Mock Catalogs

Author(s):
Hahn, ChangHoon
Abstract:
The Molino suite contains 75,000 galaxy mock catalogs designed to quantify the information content of any cosmological observable for a redshift-space galaxy sample. They are constructed from the Quijote N-body simulations (Villaescusa-Navarro et al. 2020) using the standard Zheng et al. (2007) Halo Occupation Distribution (HOD) model. The fiducial HOD parameters are based on the SDSS high luminosity samples. The suite contains 15,000 mocks at the fiducial cosmology and HOD parameters for covariance matrix estimation. It also includes (500 N-body realizations) x (5 HOD realizations)=2,500 mocks at 24 other parameter values to estimate the derivative of the observable with respect to six cosmological parameters (Omega_m, Omega_b, h, n_s, sigma_8, and M_nu) and five HOD parameters (logMmin, sigma_logM, log M_0, alpha, and log M_1). Using the covariance matrix and derivatives calculated from Molino, one can derive Fisher matrix forecasts on the cosmological parameters marginalized over HOD parameters.
Type:
Dataset
Issue Date:
November 2020

38. Theory of the tertiary instability and the Dimits shift from reduced drift-wave models

Author(s):
Zhu, Hongxuan; Zhou, Yao; Dodin, I. Y.
Abstract:
Tertiary modes in electrostatic drift-wave turbulence are localized near extrema of the zonal velocity $U(x)$ with respect to the radial coordinate $x$. We argue that these modes can be described as quantum harmonic oscillators with complex frequencies, so their spectrum can be readily calculated. The corresponding growth rate $\gamma_{\rm TI}$ is derived within the modified Hasegawa--Wakatani model. We show that $\gamma_{\rm TI}$ equals the primary-instability growth rate plus a term that depends on the local $U''$; hence, the instability threshold is shifted compared to that in homogeneous turbulence. This provides a generic explanation of the well-known yet elusive Dimits shift, which we find explicitly in the Terry--Horton limit. Linearly unstable tertiary modes either saturate due to the evolution of the zonal density or generate radially propagating structures when the shear $|U'|$ is sufficiently weakened by viscosity. The Dimits regime ends when such structures are generated continuously.
Type:
Dataset
Issue Date:
January 2020

39. Theory of the tertiary instability and the Dimits shift within a scalar model

Author(s):
Zhu, Hongxuan; Zhou Yao; Dodin, I.Y.
Abstract:
The Dimits shift is the shift between the threshold of the drift-wave primary instability and the actual onset of turbulent transport in magnetized plasma. It is generally attributed to the suppression of turbulence by zonal flows, but developing a more detailed understanding calls for consideration of specific reduced models. The modified Terry--Horton system has been proposed by St-Onge [J. Plasma Phys. {\bf 83}, 905830504 (2017)] as a minimal model capturing the Dimits shift. Here, we use this model to develop an analytic theory of the Dimits shift and a related theory of the tertiary instability of zonal flows. We show that tertiary modes are localized near extrema of the zonal velocity $U(x)$, where $x$ is the radial coordinate. By approximating $U(x)$ with a parabola, we derive the tertiary-instability growth rate using two different methods and show that the tertiary instability is essentially the primary drift-wave instability modified by the local $U''$. Then, depending on $U''$, the tertiary instability can be suppressed or unleashed. The former corresponds to the case when zonal flows are strong enough to suppress turbulence (Dimits regime), while the latter corresponds to the case when zonal flows are unstable and turbulence develops. This understanding is different from the traditional paradigm that turbulence is controlled by the flow shear $U'$. Our analytic predictions are in agreement with direct numerical simulations of the modified Terry--Horton system.
Type:
Dataset
Issue Date:
June 2020

40. Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

Author(s):
Mark D. Boyer
Abstract:
One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.
Type:
Dataset
Issue Date:
May 2020

41. Vertical forces during VDEs in an ITER plasma and the role of halo currents

Author(s):
Clasuer, C; Jardin, S; Ferraro, N
Abstract:
Vertical displacement events (VDEs) can occur in elongated tokamaks causing large currents to flow in the vessel and other adjacent metallic structures. To better understand the potential magnitude of the associated forces and the role of the so called ``halo currents'' on them, we have used the M3D-C1 code to simulate potential VDEs in ITER. We used actual values for the vessel resistivity and pre-quench temperatures and, unlike most of the previous studies, the halo region is naturally formed by triggering the thermal quench with an increase in the plasma thermal conductivity. We used the 2D non-linear version of the code and vary the post-thermal quench thermal conductivity profile as well as the boundary temperature in order to generate a wide range of possible cases that could occur in the experiment. We also show that, for a similar condition, increasing the halo current does not increase the total force on the wall since it is offset by a decrease in the toroidal contribution.
Type:
Dataset
Issue Date:
February 2020

42. Visual Analogy Extrapolation Challenge (VAEC)

Author(s):
Webb, Taylor; Dulberg, Zachary; Frankland, Steven; Petrov, Alexander; O'Reilly, Randall; Cohen, Jonathan
Abstract:
Extrapolation -- the ability to make inferences that go beyond the scope of one's experiences -- is a hallmark of human intelligence. By contrast, the generalization exhibited by contemporary neural network algorithms is largely limited to interpolation between data points in their training corpora. In this paper, we consider the challenge of learning representations that support extrapolation. We introduce a novel visual analogy benchmark that allows the graded evaluation of extrapolation as a function of distance from the convex domain defined by the training data. We also introduce a simple technique, context normalization, that encourages representations that emphasize the relations between objects. We find that this technique enables a significant improvement in the ability to extrapolate, considerably outperforming a number of competitive techniques.
Type:
Dataset and Image
Issue Date:
2020