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301. Dynamic reconfiguration of the default mode network during narrative comprehension

Author(s):
Simony, Erez; Honey, Christopher; Chen, Janice; Lositsky, Olga; Yeshurun, Yaara; Wiesel, Ami; Hasson, Uri
Abstract:
Does the default mode network (DMN) reconfigure to encode information about the changing environment? This question has proven difficult, because patterns of functional connectivity reflect a mixture of stimulus-induced neural processes, intrinsic neural processes and non-neuronal noise. Here we introduce inter-subject functional correlation (ISFC), which isolates stimulus-dependent inter-regional correlations between brains exposed to the same stimulus. During fMRI, we had subjects listen to a real-life auditory narrative and to temporally scrambled versions of the narrative. We used ISFC to isolate correlation patterns within the DMN that were locked to the processing of each narrative segment and specific to its meaning within the narrative context. The momentary configurations of DMN ISFC were highly replicable across groups. Moreover, DMN coupling strength predicted memory of narrative segments. Thus, ISFC opens new avenues for linking brain network dynamics to stimulus features and behaviour.
Type:
Dataset
Issue Date:
18 July 2016

314. Raw Data for GrsA Sub-domain Dynamics

Author(s):
Sun, Xun; Alfermann, Jonas; Li, Hao; Watkins, Maxwell B.; Chen, Yi-Tsao; Chu, Jhih-Wei; Ando, Nozomi
Abstract:
This repository contains the raw photon-by-photon single-molecule FRET (smFRET) trajectories, SAXS data, and MD simulation trajectories, multi-sequence alignment, and gel images for the paper titled "Sub-Domain Dynamics Enables Chemical Chain Reactions in Nonribosomal Peptide Synthetases."
Type:
Dataset
Issue Date:
2 August 2023

315. Enhancement of edge turbulence concomitant with ELM suppression during boron powder injection in EAST

Author(s):
Sun, Zhen; Maingi, Rajesh; Diallo, Ahmed; Xu, Wei; Qian, Yuzhong; Tritz, Kevin; Ye, Yang; Li, Chenglong; Xu, Zong; Wang, Yifeng; Ye, Kaixuan; Bortolon, A.; Nagy, Alex; Zhang, Ling; Duan, Yanmin; Lu, Zhiyuan; Wang, Huiqian; Shi, Tonghui; Zhao, Hailin; Wei, Gao; Xu, Jichan; Chen, Ran; Huang, Ming; Zuo, Guizhong; Xu, Guosheng; Gong, Xianzu; Hu, Jiansheng
Type:
Dataset
Issue Date:
2021

316. Type-I ELM mitigation by continuous lithium granule gravitational injection into the upper tungsten divertor in EAST

Author(s):
Sun, Zhen; Yuzhong, Qian; Maingi, Rajesh; Wang, Yifeng; Wang, Yumin; Nagy, Alexander; Tritz, Kevin; Lunsford, Robert; Gilson, Erik; Zuo, Guizhong; Xu, Wei; Huang, Ming; Meng, Xiancai; Mansfield, Dennis K.; Zang, Qing; Zhu, Xiang; Lin, Xin; Liu, Haiqing; Duan, Yanmin; Zhang, Ling; Lyu, Bo; Liu, Yong; Wang, Liang; Bortolon, Alessandro; Xu, Guosheng; Gong, Xianzu; Hu, Jiansheng
Type:
Dataset
Issue Date:
2021

321. Supplement to PhD Dissertation: "Subsurface Computational Modeling and Policy Analysis of Large-Scale Carbon Capture, Utilization, and Storage (2022)"

Author(s):
Tao, Yiheng
Abstract:
This dataset contains supplementary materials for Chapter 4 and Chapter 5 of Yiheng Tao's PhD dissertation (2022). The dissertation’s abstract is provided here: Carbon capture, utilization, and storage (CCUS) mitigates climate change by capturing carbon dioxide (CO2) emissions from large point sources, or CO2 from the ambient air, and subsequently reusing the captured CO2 or injecting it into deep geological formations for long-term and secure storage. Almost all current decarbonization pathways include large-scale CCUS, on the order of a billion tonnes (Gt) of CO2 captured and stored each year globally starting in 2030, yet the actual deployment has lagged far behind (around 0.04 Gt CO2 was captured in 2021). In this dissertation, I contribute to several aspects of largescale deployment of CCUS by (1) developing and applying efficient numerical models to simulate geological CO2 storage and (2) identifying key policies to address the bottlenecks of overall CCUS deployment. This dissertation concerns the United States, China, and the Belt and Road Initiative (BRI) region through research projects that are consistent with each location’s current development stage of CCUS. Chapters 2 and 3 contain computational modeling studies. In Chapter 2, I develop a new series of vertical-equilibrium (VE) models in the dual-continuum modeling framework to simulate CO2 injection and migration in fractured geological formations. Those models are shown to be effective and efficient when properties of the formation allow for the VE assumption. In Chapter 3, I apply a VE model to simulate basin-scale CO2 injection in the Junggar Basin of Northwestern China. The results show that current regional emissions of more than 100 million tonnes of CO2 per year can be stored effectively, thereby confirming the great potential of the Junggar Basin for early CCUS deployment. Chapters 4 and 5 contain policy analyses. In Chapter 4, I propose a dynamic system consisting of new CO2 pipelines and novel Allam-cycle power plants in the Central United States, and examine how government policies, including an extended Section 45Q tax credit, may improve the economic feasibility of this system. Lastly, in Chapter 5, I investigate and quantify CO2 emissions implications of power plant projects associated with the BRI. I also propose a “greenness ratio” to measure the level of environmental sustainability of BRI in the power sector.
Type:
Dataset
Issue Date:
18 May 2022

322. 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

325. bitKlavier Grand Sample Library—Harp Omni Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

326. bitKlavier Grand Sample Library—House ORTF Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

327. bitKlavier Grand Sample Library—House Wide Cardioid Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

328. bitKlavier Grand Sample Library—Lip Cardioid Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

329. bitKlavier Grand Sample Library—Stage Lid ORTF Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

330. bitKlavier Grand Sample Library—Stage Lid Omni Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

331. bitKlavier Grand Sample Library—Tail Omni Mic Image

Author(s):
Trueman, Daniel
Abstract:
The bitKlavier Grand consists of sample collections of a new Steinway D grand piano from nine different stereo mic images, with: 16 velocity layers, at every minor 3rd (starting at A0); Hammer release samples; Release resonance samples; Pedal samples. Release packages at 96k/24bit, 88.2k/24bit, 48k/24bit, 44.1k/16bit are available for various applications.
Type:
Dataset and Sound
Issue Date:
24 March 2022

332. Supplementary Model Output to "Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone"

Author(s):
Trugman, Anna
Abstract:
This dataset contains all the model output used to generate the figures and data reported in the article "Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone". The data was generated during spring 2015 using the a modified version of the Ecosystem Demography model version 2, provided as a supplement accompanying the article. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
Type:
Dataset
Issue Date:
2016

340. 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

345. Data for Coarse-grained Intrinsically Disordered Proteins

Author(s):
Webb, Michael; Patel, Roshan; Borca, Carlos
Abstract:
This distribution compiles numerous physical properties for 2,585 intrinsically disordered proteins (IDPs) obtained by coarse-grained molecular dynamics simulation. This combination comprises "Dataset A" as reported in "Featurization strategies for polymer sequence or composition design by machine learning" by Roshan A. Patel, Carlos H. Borca, and Michael A. Webb (DOI: 10.1039/D1ME00160D). The specific IDP sequences are sourced from version 9.0 of the DisProt database. The simulations were performed using the LAMMPS molecular dynamics engine. The interactions used for simulation are obtained from R. M. Regy , J. Thompson , Y. C. Kim and J. Mittal , Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins, Protein Sci., 2021, 1371 —1379.
Type:
Dataset
Issue Date:
6 May 2022

346. Data for Configurations and Characteristics of Simulated Single-Chain Nanoparticles

Author(s):
Webb, Michael; Patel, Roshan; Colmenares, Sophia
Abstract:
This item provides access to all configurations of single-chain nanoparticles analyzed in the manuscript "Sequence Patterning, Morphology, and Dispersity in Single-Chain Nanoparticles: Insights from Simulation and Machine Learning" by Roshan A. Patel, Sophia Colmenares, and Michael A. Webb (DOI: 10.1021/acspolymersau.3c00007). The single-chain nanoparticles derive from 320 unique precursor chains that are distinguished by the fraction of linker beads that decorate a fixed-length polymer backbone and the distribution or blockiness of those linker beads. The data is provided in the form of serialized object using the `pickle' python module. The data was compiled using Python version 3.8.8 and Clang 10.0.0. The Python object loaded from the .pkl file is a nested list, with the first dimension having 7,680 entries for the 7,680 unique single-chain nanoparticles produced in the aforementioned paper. Each of those 7,680 entries is itself a list with 20 entries, representing the 20 different simulation snapshots of the given single-chain nanoparticle. Each of the 20 entries is another list with two entries, with the first being a numpy.ndarray containing the x,y,z coordinates of all the beads comprising the single-chain nanoparticle and the second being a numpy.ndarray with a numerical encoding to indicate whether the beads are backbone (indicated as '0') or linker beads (indicated as '1'). Altogether, this provides 153,600 configurations of single-chain nanoparticles.
Type:
Dataset
Issue Date:
2 June 2023

347. Data on Enzyme Activity Retention in glucose oxidase, lipase, and horseradish peroxidase

Author(s):
Webb, Michael; Patel, Roshan; Gormley, Adam; Tamasi, Matt; Borca, Carlos; Kosuri, Shashank
Abstract:
This distribution contains experimentally measured data for the extent of retained enzyme activity post thermal stressing for three distinct enzymes: glucose oxidase, lipase, and horseradish peroxidase. The data is used to form conclusions and develop machine learning models as reported in the publication "Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids" by Matthew Tamasi, Roshan Patel, Carlos Borca, Shashank Kosuri, Heloise Mugnier, Rahul Upadhya, N. Sanjeeva Murthy, Michael Webb*, and Adam Gormley. Details regarding the experimental protocols are reported in the aforementioned paper but are briefly discussed in the README.
Type:
Dataset
Issue Date:
17 May 2022

348. Thermodynamic and Dynamics Data for Coarse-grained Intrinsically Disordered Proteins Generated by Active Learning

Author(s):
Webb, Michael; Jacobs, William; An, Yaxin; Oliver, Wesley
Abstract:
This distribution compiles thermodynamic and (where available) dynamic properties of short protein sequences as obtained from coarse-grained molecular dynamics simulations. The dataset features 2114 protein sequences with sequence lengths ranging from N=20 up to N=50 amino acids. The simulation and analysis of these sequences is described in "Active learning of the thermodynamics--dynamics tradeoff in protein condensates'' by Yaxin An, Michael A. Webb*, and William M. Jacobs* (https://doi.org/10.48550/arXiv.2306.03696). Of the 2114 protein sequences, 80 are homomeric polypeptides (replicating a single amino acid for N = 20, 30, 40, and 50), 1266 are sourced from version 9.0 of the DisProt database, and the remaining 768 sequences are novel sequences generated during an active learning campaign described in the aforementioned manuscript. The simulations were performed using the LAMMPS molecular dynamics engine. The interactions used for simulation are obtained from R. M. Regy , J. Thompson , Y. C. Kim and J. Mittal , Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins, Protein Sci., 2021, 1371 —1379. Properties included in this distribution include second virial coefficients, pressure-density data, expectation for phase behavior at 300 K, estimated condensed-phase densities at 300 K (if exist), and condensed-phase self-diffusion coefficients at 300 K (if exist).
Type:
Dataset
Issue Date:
6 June 2023

349. 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

351. Molecular Dynamics Trajectories and Analysis Code Demonstrating Liquid-Liquid Criticality in the WAIL Water Model

Author(s):
Weis, Jack
Abstract:
These GROMACS trajectories show the existence of a critical point in deeply supercooled WAIL water. Also included is the code necessary to reproduce the figures in the corresponding paper from these trajectories. From this data the critical temperature, pressure, and density of the model can be found, and critical fluctuations in the deeply supercooled liquid can be directly observed (in a computer-simulation sense).
Type:
Dataset
Issue Date:
13 May 2022

357. Data set for "NAPS: Integrating pose estimation and tag-based tracking"

Author(s):
Wolf, Scott W.
Abstract:
Data set corresponding to "NAPS: Integrating pose estimation and tag-based tracking." This dataset contains the corresponding videos, tracking scripts, and SLEAP models along with SLEAP, NAPS, and ArUco tracking results.
Type:
Dataset
Issue Date:
7 December 2022

360. Data Files for "Declining Chinese Attitudes toward the United States amid COVID-19"

Author(s):
Xie, Yu; Huang, Junming; He, Yuchen; Yang, Feng; Zhou, Yi; Qian, Yue; Cai, Weicheng; Zhou, Jie
Abstract:
This dataset encompasses three distinct sets of data analyzed in the study, namely the survey data on favorability to the US, the survey data on trust in Americans, and the social media data.
Type:
Dataset
Issue Date:
December 2023

361. Data for "Caught in the Crossfire: Fears of Chinese-American Scientists"

Author(s):
Xie, Yu; Lin, Xihong; Li, Ju; He, Qian; Huang, Junming
Abstract:
This dataset encompasses two distinct sets of data analyzed in the study, namely Asian American Scholar Forum survey data and Microsoft Academic Graph bibleometrics data: Yu Xie, Xihong Lin, Ju Li, Qian He, Junming Huang, Caught in the Crossfire: Fears of Chinese-American Scientists, Proceedings of the National Academy of Sciences, in press (2023).
Type:
Dataset
Issue Date:
May 2023

368. Climate Impacts from Large Volcanic Eruptions in a High-resolution Climate Model: the Importance of Forcing Structure

Author(s):
Yang, Wenchang; Vecchi, Gabriel; Fueglistaler, Stephan; Horowitz, Larry; Luet, David; Muñoz, Ángel; Paynter, David; Underwood, Seth
Abstract:
Explosive volcanic eruptions have large climate impacts, and can serve as observable tests of the climatic response to radiative forcing. Using a high resolution climate model, we contrast the climate responses to Pinatubo, with symmetric forcing, and those to Santa Maria and Agung, which had meridionally asymmetric forcing. Although Pinatubo had larger global-mean forcing, asymmetric forcing strongly shifts the latitude of tropical rainfall features, leading to larger local precipitation/TC changes. For example, North Atlantic TC activity over is enhanced/reduced by SH-forcing (Agung)/NH-forcing (Santa Maria), but changes little in response to the Pinatubo forcing. Moreover, the transient climate sensitivity estimated from the response to Santa Maria is 20% larger than that from Pinatubo or Agung. This spread in climatic impacts of volcanoes needs to be considered when evaluating the role of volcanoes in global and regional climate, and serves to contextualize the well-observed response to Pinatubo.
Type:
Dataset
Issue Date:
2019

369. Calibrated VIC Model Parameters over CONUS

Author(s):
Yang, Yuan; Pan, Ming; Beck, Hylke; Fisher, Colby; Beighley, R. Edward; Kao, Shih-Chieh; Hong, Yang; Wood, Eric
Abstract:
Conventional basin-by-basin approaches to calibrate hydrologic models are limited to gauged basins and typically result in spatially discontinuous parameter fields. Moreover, the consequent low calibration density in space falls seriously behind the need from present-day applications like high resolution river hydrodynamic modeling. In this study we calibrated three key parameters of the Variable Infiltration Capacity (VIC) model at every 1/8° grid-cell using machine learning-based maps of four streamflow characteristics for the conterminous United States (CONUS), with a total of 52,663 grid-cells. This new calibration approach, as an alternative to parameter regionalization, applied to ungauged regions too. A key difference made here is that we tried to regionalize physical variables (streamflow characteristics) instead of model parameters whose behavior may often be less well understood. The resulting parameter fields no longer presented any spatial discontinuities and the patterns corresponded well with climate characteristics, such as aridity and runoff ratio. The calibrated parameters were evaluated against observed streamflow from 704/648 (calibration/validation period) small-to-medium-sized catchments used to derive the streamflow characteristics, 3941/3809 (calibration/validation period) small-to-medium-sized catchments not used to derive the streamflow characteristics) as well as five large basins. Comparisons indicated marked improvements in bias and Nash-Sutcliffe efficiency. Model performance was still poor in arid and semiarid regions, which is mostly due to both model structural and forcing deficiencies. Although the performance gain was limited by the relative small number of parameters to calibrate, the study and results here served as a proof-of-concept for a new promising approach for fine-scale hydrologic model calibrations.
Type:
Dataset
Issue Date:
4 September 2019

372. Amplification of local changes along the timescale processing hierarchy

Author(s):
Yeshurun, Yaara; Nguyen, Mai; Hasson, Uri
Abstract:
Small changes in word choice can lead to dramatically different interpretations of narratives. How does the brain accumulate and integrate such local changes to construct unique neural representations for different stories? In this study we created two distinct narratives by changing only a few words in each sentence (e.g. “he” to “she” or “sobbing” to “laughing”) while preserving the grammatical structure across stories. We then measured changes in neural responses between the two stories. We found that the differences in neural responses between the two stories gradually increased along the hierarchy of processing timescales. For areas with short integration windows, such as early auditory cortex, the differences in neural responses between the two stories were relatively small. In contrast, in areas with the longest integration windows at the top of the hierarchy, such as the precuneus, temporal parietal junction, and medial frontal cortices, there were large differences in neural responses between stories. Furthermore, this gradual increase in neural difference between the stories was highly correlated with an area’s ability to integrate information over time. Amplification of neural differences did not occur when changes in words did not alter the interpretation of the story (e.g. “sobbing” to “crying”). Our results demonstrate how subtle differences in words are gradually accumulated and amplified along the cortical hierarchy as the brain constructs a narrative over time.
Type:
Dataset
Issue Date:
August 2017

377. Lower Hybrid Drift Waves During Guide Field Reconnection

Author(s):
Yoo, Jongsoo; Ji, Jeong-Young; Ambat, M.V.; Wang, Shan; Ji, Hantao; Lo, Jenson; Li, Bowen; Ren, Yang; Jara-Almonte, J.; Fox, William; Yamada, Masaaki; Alt, Andrew; Goodman, Aaron
Type:
Dataset
Issue Date:
2020

381. Data Files for "Arranged Cohabitation among Chinese Muslims"

Author(s):
Yu, Xie; Qing, Lai; Zheng, Mu
Abstract:
Data from the 2007 Developmental Idealism survey conducted in Gansu province in China's northwestern borderlands reveal that Muslims of the Hui and Dongxiang ethnicities reported much higher rates of cohabitation experience than the secular majority Han. Based on follow-up qualitative interviews, we found the answer to lie in the interplay between the highly interventionist Chinese state and the robust cultural resilience of local Islamic communities. Using the 2000 census data and the 2010 China Family Panel Studies data, we further show that women in almost all ten Muslim ethnic groups have higher percentages of underage births and premarital births than Han women, both nationally and in the northwest where most Chinese Muslims live. As the once-outlawed behavior of cohabitation became more socially acceptable during the reform and opening-up era, young Muslim Chinese often found themselves in “arranged cohabitations” as de facto marriages formed at younger-than-legal ages.
Type:
Dataset
Issue Date:
January 2024

382. Data for "Declining Chinese Attitudes toward the United States amid COVID-19"

Author(s):
Yu, Xie; Feng, Yang; Junming, Huang; Yuchen, He; Yi, Zhou; Yue, Qian; Weicheng, Cai; Jie, Zhou
Abstract:
This dataset encompasses three distinct sets of data analyzed in the study, namely the survey data on favorability to the US, the survey data on trust in Americans, and the social media data. The first part of the dataset comprises the analysis in Study 1 and Study 3, which is collected from three surveys, including the Social Attitude Questionnaire of Urban and Rural Residents (SAQURR) in 2019 and 2020, the COVID-19 Multi-Wave Study (CMWS) between 2020 and 2022, and the Survey on Living Conditions (SLC) in 2023. The second part of the datasets provides information used in Study 4, involving the 2018 and 2020 waves of the CFPS, Baidu Index data, and the COVID-19 cases and deaths data. The third dataset is provided to depict trends in attitudes toward the US in Study 2.
Type:
Dataset
Issue Date:
March 2024

383. Data from "Transferability of data-driven, many-body models for CO2 simulations in the vapor and liquid phases"

Author(s):
Yue, Shuwen; Riera, Marc
Abstract:
This dataset comprises of data associated with the publication "Transferability of data-driven, many-body models for CO2 simulations in the vapor and liquid phases", which can be found at https://doi.org/10.1063/5.0080061. The data includes calculations for a Many-Body decomposition, virial coefficient calculations, orientational molecular scan energies, potential energy fields, correlation plots of training and testing data, vapor-liquid equilibrium simulations, liquid density simulations, and solid cell simulations.
Type:
Dataset
Issue Date:
30 March 2022

387. Data for 'Environmental Benefits and Household Costs of Clean Heating Options in Northern China'

Author(s):
Zhou, Mi; Peng, Liqun; Zhang, Lin; Mauzerall, Denise L.
Abstract:
This dataset is created for the paper titled 'Environmental Benefits and Household Costs of Clean Heating Options in Northern China' and published on Nature Sustainability. Based on a 2015 regional anthropogenic emission inventory (base case), we propose seven counterfactual scenarios in which all 2015 residential solid fuel heating in northern China switches to one of the following non-district heating options: clean coal with improved stoves (CCIS), natural gas heaters (NGH), resistance heaters (RH), or air-to-air heat pumps (AAHP). This dataset provides the following gridded information for the base case and each clean heating scenario: (1) annual residential heating emissions for PM2.5/NOx/SO2; (2) monthly mean surface PM2.5 concentrations from the WRF-Chem model; (3) annual PM2.5-related premature deaths calculated by the GEMM model; (4) 2015 population in China; (5) mask for provinces in China; (6) longitude and latitude of each grid center.
Type:
Dataset
Issue Date:
22 December 2021

398. Blob wakes in NSTX

Author(s):
Zweben, S. J.; Myra, J. R.; Diallo, A.; Russell, D. A.; Scotti, F.; Stotler, D. P.
Type:
Dataset
Issue Date:
2019