UMD Data Collection

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University of Maryland faculty and researchers can upload their research products in DRUM for rapid dissemination, global visibility and impact, and long-term preservation. Depositing data in DRUM can assist in compliance with data management and sharing requirements from the NSF, NIH, and other funding agencies and journals. You can also deposit code, documents, images, supplemental material, and other research products. DRUM tracks views and downloads of your research, and all DRUM records are indexed by Google and Google Scholar. Additionally, DRUM assigns permanent DOIs for your items, making it easy for other researchers to cite your work.

Submissions to the Data Collection

To add files to the UMD Data Collection, submit a new item through your associated department or program's DRUM collection and check the box indicating your upload contains a dataset.

Find more information and guidelines for depositing into the Data Collection on the University of Maryland Libraries' DRUM for Data page.

Assistance

Please direct questions regarding the UMD Data Collection or assistance in preparing and depositing data to the Data Services Librarian: lib-research-data@umd.edu.

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Recent Submissions

Now showing 1 - 5 of 128
  • Item
    Emotions in Polish and Lithuanian Social Media
    (2023) Paletz, Susannah B. F.; Rytting, C. Anton; Johns, Michael A.; Pandža, Nick B.; Golonka, Ewa M.; Murauskaite, Egle E.; Buntain, Cody
    We applied modern psychology theory of emotions and cross-cultural psychology methods to a range of issues surrounding emotions and social media. We developed an annotation guide for three languages and identified 365 Polish and 188 Lithuanian sociopolitical entities, and we developed a consensus annotated corpus for over 3,000 Polish and over 1,500 Lithuanian Facebook posts for emotional content, primary topic, post shares, and more. This corpus represents data we intend to have as sharable that was used in papers we hope to publish. More detail can be gained by reading the methodology description and by contacting the study PI, Susannah Paletz, at paletz@umd.edu.
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    Supplementary materials for positive-unlabeled learning identifies vaccine candidate antigens in the malaria parasite Plasmodium falciparum
    (2023) Chou, Renee Ti; Ouattara, Amed; Adams, Matthew; Berry, Andrea A.; Takala-Harrison, Shannon; Cummings, Michael P.
    Malaria vaccine development is hampered by extensive antigenic variation and complex life stages of Plasmodium species. Vaccine development has focused on a small number of antigens identified prior to availability of the P. falciparum genome. In this study, we implement a machine learning-based reverse vaccinology approach to predict potential new malaria vaccine candidate antigens. We assemble and analyze P. falciparum proteomic, structural, functional, immunological, genomic, and transcriptomic data, and use positive-unlabeled learning to predict potential antigens based on the properties of known antigens and remaining proteins. We prioritize candidate antigens based on model performance on reference antigens with different genetic diversity and quantify the protein properties that contribute the most to identifying top candidates. Candidate antigens are characterized by gene essentiality, gene ontology, and gene expression in different life stages to inform future vaccine development. This approach provides a framework for identifying and prioritizing candidate vaccine antigens for a broad range of pathogens.
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    9M Parent Math Talk Codes
    (2023-04-10) Mix, Kelly; Cabrera, Natasha
    The dataset contains parent math talk scores derived from coding of videorecorded home visits (Cabrera & Reich, 2017) completed when children were 9 months of age, as well as numeracy outcome scores collected when children were 42 months old. Coding was completed between June 2021 and December, 2022.
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    Effects of Aging on Cortical Representations of Continuous Speech
    (2022) Karunathilake, I.M Dushyanthi; Simon, Jonathan Z.
    Understanding speech in a noisy environment is crucial in day-to-day interactions, and yet becomes more challenging with age, even for healthy aging. Age-related changes in the neural mechanisms that enable speech-in-noise listening have been investigated previously; however, the extent to which age affects the timing and fidelity of encoding of target and interfering speech streams are not well understood. Using magnetoencephalography (MEG), we investigated how continuous speech is represented in auditory cortex in the presence of interfering speech, in younger and older adults. Cortical representations were obtained from neural responses that time-locked to the speech envelopes using speech envelope reconstruction and temporal response functions (TRFs). TRFs showed three prominent peaks corresponding to auditory cortical processing stages: early (~50 ms), middle (~100 ms) and late (~200 ms). Older adults showed exaggerated speech envelope representations compared to younger adults. Temporal analysis revealed both that the age-related exaggeration starts as early as ~50 ms, and that older adults needed a substantially longer integration time window to achieve their better reconstruction of the speech envelope. As expected, with increased speech masking, envelope reconstruction for the attended talker decreased and all three TRF peaks were delayed, with aging contributing additionally to the reduction. Interestingly, for older adults the late peak was delayed, suggesting that this late peak may receive contributions from multiple sources. Together these results suggest that there are several mechanisms at play compensating for age-related temporal processing deficits at several stages, but which are not able to fully reestablish unimpaired speech perception.
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    Experimental Demonstration and Quantification of Electrostatic Lofting of Dust Clumps
    (2023) Pett, Charles; Hartzell, Christine; Hartzell, Christine
    Electrostatic lofting of individual regolith grains on the Moon and asteroids has been investigated extensively. However, motion of clumps has been mentioned only anecdotally. For the first time, we electrostatically lofted clumps of 200-300 micrometer zirconia-silica microspheres in vacuum and quantitatively analyzed their trajectories. The microspheres were charged by an emissive filament. A biased plate produced an electric field of 870 kV/m that attracted sufficiently charged clumps from the surface. A high-speed camera imaged the lofted clumps at 945 fps in order to obtain their size and centroid positions over time. Using the centroids from the initial clump detachment, we numerically calculated an initial acceleration to solve for the cohesion that had been restraining the clump. These experimental results show that the detachment of clumps of particles are a non-negligible portion of the lofted object population for cohesive powders. Thus, if electrostatic lofting occurs on small airless bodies, we will likely see clumps lofted.