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221. 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

222. 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

223. 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

224. 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

225. 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

226. 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

227. 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

228. 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

229. 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

230. 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