Interest in quantitative imaging of Y-90 is growing because transarterial radioembolization (RE) with Y-90 loaded microspheres is a promising and minimally invasive treatment that is FDA approved for unresectable primary and metastatic liver tumors. These cancers are a leading cause of cancer mortality and morbidity. Radioembolization is a therapy that irradiates liver tumors with radioactive microspheres administered through a microcatheter placed in the hepatic arterial vasculature. Radioembolization is based on the principle that healthy liver and tumor are mainly vascularized by the portal vein and the hepatic artery respectively. As a result, radioactive microspheres are preferentially located in the lesions after they are administered via the hepatic artery.
Van, B. J., Dewaraja, Y. K., Sangogo, M. L., & Mikell, J. K. (2021). Y-90 SIRT: Evaluation of TCP variation across dosimetric models. EJNMMI Physics, 8(1), 45. https://doi.org/10.1186/s40658-021-00391-6
In a broad sense, this project explores morphological and phonological processing in English monolinguals and two bilingual populations, Chinese-English and Spanish-English, using a battery of standardized and self-developed behavioral measures, as well as fNIRS neuroimaging. (T1=NEW PARTICIPANTES -TESTED BEHAVIORAL AND fNIRS-, T2= RETURNING PARTICIPANTS -JUST TESTED WITH BEHAVIORAL ASSESSMENTS)
In a broad sense, this dataset explores morphological and phonological processing in English monolinguals and two bilingual populations, Chinese-English and Spanish-English, using a battery of standardized and self-developed behavioral measures.
Language: English - Spanish - Chinese
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.
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
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
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
The goal of this research is to investigate the impact of fast formation protocol on battery lifetime.
The dataset has also been used to explore data-driven approaches in battery lifetime estimation (manuscript under review). Source code used to generate the results for this work has been included.
The file contents contain a detailed README.md file which describes the organization of the files.
This dataset consists of 11 linear external morphological measurements from 2,593 adult frog individuals from 757 species. We use these data to investigate patterns and rates of frog size and shape evolution. The measured traits are predictive of adult microhabitat use, diel activity patterns, locomotion, mating habitat, and diet.
We created various files, including GIS files and data files for both the UM Hydrologic Modeling Team and for our own Escherichia coli sampling project. The UM Hydrologic Team used the files we created to make their models more accurate. For example, we edited Clinton River subwatershed files to better reflect below and above-ground infrastructure, and provided them to the modeling team. For our own E. coli subproject we created time series, GIS files, and R code to better understand the influence of precipitation and streamflow on E. coli dynamics. Our time-series data is based on baseline and storm sampling we conducted in the summer of 2021. We used GIS files to explore the subwatersheds of our E. coli sampling locations. Finally, we created R code to help us visualize and analyze the data.