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University of South Florida

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1970
2023
1970 2023
4911 results
  • Noise Signature Identification (Ambient Sounds in the University of South Florida, EBII)
    We recorded the ambient sound of several rooms of the Engineering Building II of the University of South Florida. After filtering the sample to isolate ambient noise, we trained the system using both binary classification -whether or not an audio sample belonged to a specific room- and multi-class classification, which room out of the 19 possible rooms, hallways, entries, and meeting spaces does the audio sample belong to. These files contain the ARFF files used to train and test the models in Weka (https://www.cs.waikato.ac.nz/ml/weka/). They are separated by rooms to the Binary classification, except one for the Multiclass classification.
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  • Item Pool and Parameters for Definitions Project
    The current project titled, “The Effect of Definitions, Contextual Support, and Cognate Status on 4th Grade Spanish-speaking English Learners' (ELs) Understanding of Unfamiliar Words in Text”, was funded by the Institute of Education Sciences. Our research team conducted two experiments to help Spanish-speaking English learners (ELs) understand academic words in English. ELs often come across unfamiliar words when they read, which can make it challenging to comprehend what they're studying. Knowing these words is crucial for better reading and understanding. In our experiments, we tried different methods to assist ELs in learning new academic words and comprehending them when they read. We looked at how providing various types of definitions, using similar words from their native language (cognates), and offering context-related support could improve their ability to learn these words and read texts that contained them. Our findings suggest that fourth-grade Spanish-speaking ELs benefit equally from Spanish and English definitions for learning English words, but this might depend on their Spanish vocabulary skills. Students with higher Spanish vocabulary benefit more from Spanish definitions than students who are low in their overall Spanish vocabulary knowledge. The findings from these studies will guide the development of future programs designed to support Spanish-speaking ELs in building their academic vocabulary. Additionally, our research results will also influence the types of accommodations provided to ELs during assessments. Contents of the dataset include: Table 1. Item Stems and Response Options for 141 Items from the Word Definition Learning Assessment (WDLA) Item Pool Table 2. Linguistic Parameters for 141 Items from the Word Definition Learning Assessment (WDLA) Item Pool Table 3. Item Stems and Response Options for 108 Items from the Word-Meaning-in-Context (WMC) Assessment Item Pool Table 4. Linguistic Parameters for 108 Items from the Word-Meaning-in-Context (WMC) Assessment Item Pool
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  • Numerical modeling of MH370 flaperon drift based on barnacle geochemical data
    Numerical modeling simulation data for Lepas project
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  • Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients
    The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 hours of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.
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  • Radula stl files
    Specimens were scanned using single propagation distance tomography at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France using the ID19 microtomography beamline. Every specimen used the following scan parameters: 2999 projections collected for a 360° rotation; 0.1 ms exposure time; 360 nm voxel size; 20 mm sample-to-detector distance; x-ray energy of 26.5 keV. Specimen preparation for scanning electron microscopy (SEM) was the same as for synchrotron preparation except that radulae were mounted on stubs with double-sided conductive tape, and coated with Au-Pd for imaging with a Philips XL 30 scanning electron microscope at the Museo Argentino de Ciencias Naturales. Synchrotron *.tif stacks were reconstructed with Paganin phase retrieval, imported into Avizo Lite 9.4 (Thermo Fisher Scientific) and visually explored for mature rachidian teeth that showed no evidence of in vivo wear or post-mortem breaking during sample preparation. The scan volume was then cropped to these sections to facilitate easier data management. Segmentation of one tooth per species was performed semi-automatically: the “Magic Wand” tool was used initially to select the tooth volume based on greyscale intensity and then to manually remove any traces of the supporting radular membrane, mount, or mounting glue remained attached to the teeth. Once segmented, each tooth was exported as an *.stl and brought into Geomagic Wrap 2017 (3D Systems) for smoothing and cleaning of artefacts. In one specimen (Acanthais), damage to the tooth was only apparent after segmentation.
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  • CIT-Ridesharing
    Ridesharing data with 220 samples
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  • Data from: Risk of Gastroenteritis from Swimming at a Wastewater-Impacted Tropical Beach Varies across Localized Scales
    This dataset contains measurements of concentrations of MST marker HF183 and fecal indicator microorganisms (fecal coliforms and enterococci). Water samples were collected just outside the river plume in three rivers that impact a Costa Rican beach during the rainy and dry season. Microorganisms were filtered from a 500-mL grab sample onto a 0.45-µm, mixed cellulose ester. Enterococci and fecal coliforms were cultured.HF183 was quantified from nucleic acid using quantitative PCR. We examined microbiological water quality in three rivers that impact a Costa Rican beach.
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  • Microbial community dataset for sphalerite and oyster shell denitrification study
    This file includes the microbial community abundance and community change for the paper titled "Autotrophic denitrification supported sphalerite and oyster shells: Chemical and microbiome analysis."
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  • Data from: Risk of Gastroenteritis from Swimming at a Wastewater-Impacted Tropical Beach Varies across Localized Scales
    This dataset contains measurements of concentrations of pathogens, MST markers and fecal indicator microorganisms. Water samples were collected in three rivers that impact a Costa Rican beach during the rainy and dry season. Enterococci and fecal coliforms were filtered from a 500-mL grab sample onto a 0.45-µm, mixed cellulose ester. All other microorganisms were concentrated on site from 50 L of water by ultrafiltration. Enterococci, fecal coliforms, C. perfringens, male specific coliphage, somatic coliphage and Salmonella were cultured. Giardia spp. and Cryptosporidium spp. were enumerated by immunomagnetic separation and microscopy. NoVGI, AdV, HF183 and PMMoV were all quantified from nucleic acid using quantitative PCR. We examined microbiological water quality in three rivers that impact a Costa Rican beach, and the risk of illness from swimming in the rivers.
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  • Data_WallaceEtAl_Reconstructions of individual fish trophic geographies using isotopic analysis of eye-lens amino acids
    Amino-acid isotope data associated with publication entitled "Reconstructions of individual fish trophic geographies using isotopic analysis of eye-lens amino acids" by Amy A. Wallace, Greg S. Ellis, and Ernst B. Peebles
    • Tabular Data
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