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Start Over Year Published 2020 Source dataspace

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. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

17. 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

18. 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

19. 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

20. 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

21. 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

24. 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

25. 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