This repository contains both the data and python3 code that reads this data and reproduces the relevant figures. The code depends on NumPy >1.17 and matplotlib >3.1 and was tested on python 3.8
The focus of this research effort is to systematically study the capability of aging diagnostics using cell expansion under variety of aging conditions and states. The data collection campaign is very important to cover various degradation modes to extract the degradation features that will be used to inform, parameterize, and validate the models developed earlier. In the data collection campaign, we are documenting the evolution of the electrical and mechanical characteristics and especially the reversible mechanical measurement. It is important to note that we collect data using newly developed fixtures that enables the simultaneous measurement of mechanical and electrical response under pseudo-constant pressure.
Peyman Mohtat et al. (2021). Reversible and Irreversible Expansion of Lithium-ion Batteries Under a Wide Range of Stress Factors. J. Electrochem. Soc. 168 100520 https://doi.org/10.1149/1945-7111/ac2d3e
This data is a subset of the data used to generate components of all figures in the manuscript and supplement in Nason et al., 2021, Neuron. The purpose of the study was to demonstrate the first-ever simultaneous brain-control of two independent groups of fingers in one hand with some analysis of cortical tuning to finger movements in nonhuman primates. This advises future brain-machine interfaces for the control of finger movements with humans. All of the data is contained in .mat files, which can be commonly opened by Matlab and the Python scipy library. The Matlab packages (and versions) used for the manuscript are: MATLAB (9.4), Signal Processing Toolbox (8.0), Statistics and Machine Learning Toolbox (11.3), and Curve Fitting Toolbox (3.5.7).
Nason, S.R., Mender, M.J., Vaskov, A.K., Willsey, M.S., Ganesh Kumar, N., Kung, T.A., Patil, P.G., and Chestek, C.A. (2021). Real-Time Linear Prediction of Simultaneous and Independent Movements of Two Finger Groups Using an Intracortical Brain-Machine Interface. Neuron (accepted).
This data is a subset of the data used to generate figures similar to figures 1, 2, 3, and 4 in Nason et al., 2020, Nature Biomedical Engineering. The purpose of the study was to demonstrate the benefits of using spiking band power, a low-power but single unit specific recording signal, for brain-machine interfaces with nonhuman primates with the potential to impact low-power brain-machine interfaces with humans. All of the data is contained in .mat files, which can be commonly opened by Matlab and the Python scipy library.
Nason, S.R., Vaskov, A.K., Willsey, M.S., Welle, E.J., An, H., Vu, P.P., Bullard, A.J., Nu, C.S., Kao, J.C., Shenoy, K.V., Jang, T., Kim, H.-S., Blaauw, D., Patil, P.G., and Chestek, C.A. (2020). A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain–machine interfaces. Nat. Biomed. Eng. 4, 973–983. https://doi.org/10.1038/s41551-020-0591-0
The data contain the daily-averaged atmospheric concentrations of CO2 tracers in the Northern Hemisphere simulated from a tagged tracer transport model GEOS-Chem v12.0.0. Thirteen land flux regions are defined and tagged in the model to separate their imprints on the long-term atmospheric CO2 seasonal amplification in Northern Hemisphere. A file describing the delineation of these land flux regions is also provided. See the README file for more details on the dataset and model configurations.
Lin, X., Rogers, B. M., Sweeney, C., Chevallier, F., Arshinov, M., Dlugokencky, E., Machida, T., Sasakawa, M., Tans, P., & Keppel-Aleks, G. (2020). Siberian and temperate ecosystems shape Northern Hemisphere atmospheric CO2 seasonal amplification. Proceedings of the National Academy of Sciences, 117(35), 21079–21087.
This dataset includes spectrally-resolved optical properties for volcanic ash particles from the 2010 Eyjafjallajökull volcanic eruptions. These properties were used in the climate simulations described by Flanner et al. (2014, doi:10.1002/2014JD021977) to quantify ash radiative forcing from the eruptions.
This data is from a project concerned with dehydrating samples of saturated superabsorbent polymer using a centrifuge. The goal was to consider centrifugation as an energy efficient scheme to dehydrate SAP with the notion of reusing it. The data provided contains mass fractions of solvent removed through centrifugation with varied parameters.
Pine, A., Wu, C. C., Raghavan, S., & Love, B. (2021). The efficiency of dehydrating desiccants by centrifugation: An assessment of superabsorbent polymers. Drying Technology, 0(0), 1–8. https://doi.org/10.1080/07373937.2021.1939710
Conducting quantitative metrics-based performance analysis of first-principles-based global magnetosphere models is an essential step in understanding their capabilities and limitations, and providing scope for improvements in order to enhance their space weather prediction capabilities for a range of solar conditions. In this study, a detailed comparison of the performance of three global magnetohydrodynamic (MHD) models in predicting the Earth’s magnetopause location and ionospheric cross polar cap potential (CPCP) has been presented. Using the Community Coordinated Modeling Center’s Run-on-Request system and extensive database on results from various magnetospheric scenarios simulated for a variety of solar wind conditions, the aforementioned model predictions have been compared for magnetopause standoff distance estimations obtained from six empirical models, and with cross polar cap potential estimations obtained from the Assimmilative Mapping of Ionospheric Electrodynamics (AMIE) Model and the Super Dual Auroral Radar Network (SuperDARN) observations. We have considered a range of events spanning different space weather activity to analyze the performance of these models. Using a fit performance metric analysis for each event, we have quantified the models’ reproducibility of magnetopause standoff distances and CPCP against empirically-predicted observations, and identified salient features that govern the performance characteristics of the modeled magnetospheric and ionospheric quantities.
Citation to related publication:
Mukhopadhyay, A., Jia, X., Welling, D. T., & Liemohn, M. W. (2021). Global Magnetohydrodynamic Simulations: Performance Quantification of Magnetopause Distances and Convection Potential Predictions. Frontiers in Astronomy and Space Sciences, 8. https://doi.org/10.3389/fspas.2021.637197
We evaluated PM levels at the Agbogbloshie e-waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations. This monitoring forms part of the West Africa-Michigan Charter II for GEOHealth cohort study, which is analyzing occupational exposures and health risks at this site.
Kwarteng, L., Baiden, E. A., Fobil, J., Arko-Mensah, J., Robins, T., & Batterman, S. (2020). Air Quality Impacts at an E-Waste Site in Ghana Using Flexible, Moderate-Cost and Quality-Assured Measurements. GeoHealth, 4(8), e2020GH000247. https://doi.org/10.1029/2020GH000247
Student capital is the set of skills, traits, and resources that an individual can draw upon to be successful in school. With dropout rates around 50%, community college students often don't have enough student capital to achieve their goals. The R code in this dataset estimates the average student capital of a group of community college students using data on their total credits and academic outcomes. It also contains R code to create figures, as found in the paper "The Shape of Educational Inequality" by Quarles, Budak & Resnick.