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Illinois Data Bank Dataset Search Results
Dataset Search Results
planned publication date: 2025-09-01
Jang, Chunhwa; Namoi, Nictor; Lee, Jung Woo; Becker, Talon; Rooney, William; Lee, DoKyoung (2025): Data for Identifying the best high-biomass sorghum hybrids based on biomass yield potential and feedstock quality affected by nitrogen fertility management under various environments. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-0618787_V1
Data were collected from agronomy fields in Urbana and Ewing, IL, during the 2022 and 2023 growing seasons. The dataset includes dry biomass yield, nitrogen, phosphorus, and potassium concentrations and removals, and chemical composition elements (cellulose, hemicellulose, lignin, and soluble fractions) for 13 high-biomass sorghum hybrids. data_sharing.xlsx contains 20 columns and 104 rows. Below is the explanation of all variables in the file: Year: 2022; 2023 Location: Urbana, IL; Ewing, IL N rate (kg-N/ha): 0; 112 Hybrid #: H1-H13 Pedigree: Pedigree for 13 hybrids Dry biomass yield (Mg/ha): Aboveground dry biomass yield N (g/kg): Nitrogen concentration in plant tissue P (g/kg): Phosphorus concentration in plant tissue K (g/kg): Potassium concentration in plant tissue N (kg/ha): Nitrogen removal by aboveground biomass P (kg/ha): Phosphorus removal by aboveground biomass K (kg/ha): Potassium removal by aboveground biomass Cellulose (g/kg): Cellulose concentration in plant tissue Hemicellulose (g/kg): Hemicellulose concentration in plant tissue Lignin (g/kg): Lignin concentration in plant tissue Soluble (g/kg): Soluble concentration in plant tissue Cellulose (Mg/ha): Cellulose content in aboveground biomass Hemicellulose (Mg/ha): Hemicellulose content in aboveground biomass Lignin (Mg/ha): Lignin content in aboveground biomass Soluble (Mg/ha): Soluble content in aboveground biomass
keywords:
High-biomass sorghum; Biomass yield; Nutrient removal; Chemical composition: Illinois
published: 2025-07-30
Skorupa, A. J.; Bried, J. T. (2025): Data for 'Linking climate sensitivity, trait combinations, and listing status in a regional pool of freshwater invertebrates'. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-1156002_V1
This dataset includes three data files for linking species' climate sensitivity, trait combinations, and listing status. It contains species occurrence data within Hydrologic Unit Code 12 (HUC12) watersheds, along with trait information and Rarity and Climate Sensitivity (RCS) index scores for lotic caddisflies, stoneflies, mussels, dragonflies, and crayfish across all Midwest Climate Adaptation Science Center states: Minnesota, Iowa, Missouri, Wisconsin, Illinois, Indiana, Michigan, and Ohio. For mussels, the geographic scope is expanded to include all Midwest Regional Species of Greatest Conservation Need (RSGCN) states—North Dakota, South Dakota, Nebraska, Kansas, and Kentucky. However, occurrence data for mussels is not included due to data-sharing agreements. Metadata are included with each data file. Please refer to the associated manuscript for original data sources, trait references, and details on the RCS index calculation.
keywords:
climate sensitivity; conservation status; traits; aquatic invertebrates; Midwest
published: 2025-05-06
Huang, Yijing; Nick, Abboud (2025): Data for Observation of a Dynamic Magneto-chiral Instability in Photoexcited Tellurium. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-1409842_V2
Dataset and Code Description This repository provides the data and code used to reproduce key plots from the manuscript and to extend discussions that were only briefly covered therein. The dataset is organized into five subfolders. Each subfolder corresponds to a unique combination of experimental conditions, including: • Magnetic field orientation (B ∥ c or B ⟂ c) • Scan parameter (magnetic field or temperature) • Pump laser polarization (linear s, linear p, or circular) • Detection polarization (linear s) Each folder contains: • The raw time-domain data files (.mat) • Oscillator parameters extracted via linear prediction algorithm (.mat) • MATLAB scripts (.m) that generate plots of the raw data, processed fits, and amplified modes Folder summary: 1. B_parallel_c_linear_spump_sprobe_field: B ∥ c, s-polarized pump, s-polarized THz detection, magnetic field dependence 2. B_parallel_c_linear_spump_sprobe_temperature: B ∥ c, s-polarized pump, s-polarized THz detection, temperature dependence 3. B_perp_c_linear_spump_sprobe_field: B ⟂ c, s-polarized pump, s-polarized THz detection, magnetic field dependence 4. B_perp_c_linear_spump_sprobe_temperature: B ⟂ c, s-polarized pump, s-polarized THz detection, temperature dependence 5. B_parallel_c_LCPRCP_pump_sprobe_field: B ∥ c, circularly polarized pump (LCP & RCP), s-polarized THz detection, magnetic field dependence Software requirements: All scripts were developed and tested in MATLAB R2024a. Each script should be run within its corresponding folder to ensure proper loading of the associated data files.
keywords:
magneto-chiral instability; THz emission; THz spectroscopy; nonequilibrium states; emergent phenomena; Weyl semiconductor; tellurium; ultrafast spectrscopy; photoexcitation
published: 2025-07-14
Hossain, Mohammad Tanver; Piorkowski, Dakota; Lowe, Andrew; Eom, Wonsik; Shetty, Abhishek; Tawfick, Sameh; Fudge, Douglas; Ewoldt, Randy (2025): Data for Physics of Unraveling and Micromechanics of Hagfish Threads. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-6667965_V1
Data accompanying the article "Physics of Unraveling and Micromechanics of Hagfish Threads". Abstract of the article: Hagfish slime is a unique biological material composed of mucus and protein threads that rapidly deploy into a cohesive network when deployed in seawater. The forces involved in thread deployment and interactions among mucus and threads are key to understanding how hagfish slime rapidly assembles into a cohesive, functional network. Despite extensive interest in its biophysical properties, the mechanical forces governing thread deployment and interaction remain poorly quantified. Here, we present the first direct in situ measurements of the micromechanical forces involved in hagfish slime formation, including mucus mechanical properties, skein peeling force, thread–mucus adhesion, and thread–thread cohesion. Using a custom glass-rod force sensing system, we show that thread deployment initiates when peeling forces exceed a threshold of approximately 6.8 nN. To understand the flow strength required for unraveling, we used a rheo-optic setup to impose controlled shear flow, enabling us to directly observe unraveling dynamics and determine the critical shear rate for unraveling of the skeins, which we then interpreted using an updated peeling-based force balance model. Our results reveal that thread–mucus adhesion dominates over thread–thread adhesion and that deployed threads contribute minimally to bulk shear rheology at constant flow rate. These findings clarify the physics underlying the rapid, flow-triggered assembly of hagfish slime and inform future designs of synthetic deployable fiber–gel systems.
keywords:
supplementary data; hagfish slime; unraveling skeins
published: 2025-07-28
McCumber, Corinne; Salami, Malik Oyewale (2025): An attempt to identify 199 PubMed items excluded from "Analyzing the consistency of retraction indexing". University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-6684660_V1
This project investigates retraction indexing agreement in PubMed between 2024-07-03 and 2025-05-09 in order to address an API limitation that resulted in 199 items being excluded from analysis in "Analyzing the consistency of retraction indexing". PubMed was queried on 2024-07-03 and on 2025-05-09 using the search “Retracted Publication[PT]”. PubMed is only able to return 10,000 items when queried via the E-Utilities API. When the pipeline was run 2024-07-03, the search between 2020 and 2024 returned 10,199 items, meaning that an expected 199 items indexed as retracted in PubMed were excluded. This dataset uses and compares information from PubMed as of 2025-05-09 to attempt to identify those 199 items.
keywords:
retraction status; data quality; indexing; retraction indexing; metadata; meta-science; RISRS; PubMed
published: 2025-07-25
Mori, Jameson; Rivera, Nelda; Brown, William; Skinner, Daniel; Schlichting, Peter; Novakofski, Jan; Mateus-Pinilla, Nohra (2025): Pregnancy and chronic wasting disease (CWD) status for female white-tailed deer (Odocoileus virginianus) in northern Illinois, USA between fiscal years 2005 and 2024. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-6395643_V1
This dataset contains the pregnancy status of wild, white-tailed deer (Odocoileus virginianus) from northern Illinois culled as part of the Illinois Department of Natural Resources' chronic wasting disease (CWD) surveillance program. Fiscal years 2005 through 2024 are included. A fiscal year is the time between July 1st of one calendar year and June 30th of the next. Variables in this dataset include the pregnancy status, CWD infection status, age, weight, and day of mortality for each female deer, as well as the deer land cover utility (LCU) score for the TRS, township, or county from which the deer was culled. The deer population density of the county is also included. Data have been anonymized for landowner privacy reasons so that the location and year are not identifiable, but will give the same modeling results by maintaining how the data are grouped. The R code used to conduct the regression modeling is also included.
keywords:
cervid; Cervidae, chronic wasting disease; CWD; reproduction; white-tailed deer; Odocoileus virginianus; pregnancy; regression
published: 2025-07-23
Dalling, James William (2025): Data for "Soil and Biomass Carbon Storage is Much Higher in Central American than Andean Montane Forests". University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-7962588_V1
Supplementary data and code associated with the Biogeosciences paper published by Cecilia Prada et al. "Soil and Biomass Carbon Storage is Much Higher in Central American than Andean Montane Forests". There are 16 files associated with this paper (1) AGB.csv providing the site, plot, treeID, mnemn, family, agb, and AGcarbon for each tree in the dataset. Column headings are described in the file AGB_metadata.csv (2) AGB_metadata.csv Metadata (column descriptions) for AGB.csv (3) CWD_D.csv Complete information on the downed coarse woody debris (CWD) measured in each plot (4) CWD_D_metadata.csv Metadata (column descriptions) for CWD_D.csv (5) CWD_S.csv Complete information on the standing coarse woody debris measured in each plot (6) CWD_S_metadata.csv Metadata (column descriptions) for CWD_S.csv (7) SoilC.csv Estimated soil carbon storage (Mg C) at each sampling location in each plot (8) SoilC_metadata.csv Metadata (column descriptions) for SoilC.csv (9) Table.csv Data source, soil carbon value (Mg C) and elevation from published data sources (10) Table_metadata.csv Metadata (column descriptions) for Table.csv (11) TableS1.csv Data source, above ground carbon value (Mg C) and elevation from published data sources (12) TableS1_metadata.csv Metadata (column descriptions) for TableS1.csv (13) RScript.R Annotated code for data analysis and figures (14)Full_dataset.csv Full set of environmental data and carbon data by plot (15) Full_dataset_metadata.csv Metadata (column descriptions) for Full_dataset.csv (16) Species list and species codes.csv Full family, genus and species names for the species codes (column mnemn in AGB.csv)
keywords:
tropical forest; carbon storage
published: 2025-06-22
Stickley, Samuel; Crawford, John; Peterman, William; Fraterrigo, Jennifer (2025): Microclimate Species Distribution Models and Mechanistic Models of Potential Surface Activity for Plethodontid Salamanders in Great Smoky Mountains National Park. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-1162151_V1
keywords:
terrestrial salamanders, microhabitat, physiology, mechanistic models, ecological niche models, climate change, Great Smoky Mountains National Park
published: 2019-09-01
Jackson, Nicole; Konar, Megan; Debaere, Peter; Estes, Lyndon (2019): Data for: Probabilistic global maps of crop-specific areas from 1961 to 2014. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-7439710_V1
Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961-2014. The resulting database presented here provides annual global gridded likelihood estimates of crop-specific areas. Both mean and standard deviations of grid cell fractions are available for each of the 17 crops. Each netCDF file contains an individual year of data with an additional variable ("crs") that defines the coordinate reference system used. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2019) in Environmental Research Letters (https://doi.org/10.1088/1748-9326/ab3b93).
keywords:
global; gridded; probabilistic allocation; crop suitability; agricultural geography; time series
published: 2025-07-21
Feng, Jennifer T.; van den Berg, Thya; Donders, Timme H.; Kong, Shu; Puthanveetil Satheesan, Sandeep; Punyasena, Surangi W. (2025): Slide scans, annotated pollen counts, and trained pollen detection models for fossil pollen samples from Laguna Pallcacocha, El Cajas National Park, Ecuador . University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-4207757_V1
This dataset includes image stacks, annotated counts, and ground-truth masks from two high-resolution sediment cores extracted from Laguna Pallcacocha, in El Cajas National Park, Ecuadorian Andes by Moy et al. (2002) and Hagemans et al. (2021). The first core (PAL 1999, from Moy et al. (2002)) extends through the Holocene (11,600 cal. yr. BP - present). There are a total of 900 annotated image stacks and masks in the PAL 1999 domain. The second core (PAL IV, from Hagemans et al. (2021)) captures the 20th century. There are 2986 annotated image stacks and masks in the PAL IV domain. Different microscopes and annotations tools were used to image and annotate each core and there are corresponding differences in naming conventions and file formats. Thus, we organized our data separately for the PAL 1999 and the PAL IV domains. The three letter codes used to label our pollen annotations are in the file: “Pollen_Identification_Codes.xlsx”. Both domain directories contain: • Image stacks organized by subdirectory • Annotations within each image stack directory, containing specimen identifications using a three letter code and coordinates defining bounding boxes or circles • Ground-truth distance-transform masks for each image stack The zip file "bestValModel_encoder.paramOnly.zip" is the trained pollen detection model produced from the images and annotations in this dataset. Please cite this dataset as: Feng, Jennifer T.; van den Berg, Thya; Donders, Timme H.; Kong, Shu; Puthanveetil Satheesan, Sandeep; Punyasena, Surangi W. (2025): Slide scans, annotated pollen counts, and trained pollen detection models for fossil pollen samples from Laguna Pallcacocha, El Cajas National Park, Ecuador . University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-4207757_V1 Please also include citations of the original publications from which these data are taken: Feng, Jennifer T., Sandeep Puthanveetil Satheesan, Shu Kong, Timme H. Donders, and Surangi W. Punyasena. “Addressing the ‘Open World’: Detecting and Segmenting Pollen on Palynological Slides with Deep Learning.” bioRxiv, January 1, 2025. https://doi.org/10.1101/2025.01.05.631390. Feng, Jennifer T., Sandeep Puthanveetil Satheesan, Shu Kong, Timme H. Donders, and Surangi W. Punyasena. “Addressing the ‘Open World’: Detecting and Segmenting Pollen on Palynological Slides with Deep Learning.” Paleobiology, 2025 [in press]. Feng, J. T. (2023). Open-world deep learning applied to pollen detection (MS thesis, University of Illinois at Urbana-Champaign). https://hdl.handle.net/2142/120168
keywords:
continual learning; deep learning; domain gaps; open-world; palynology; pollen grain detection; taxonomic bias
published: 2024-11-12
Zinnen, Jack; Chase, Marissa; Charles, Brian; Harmon-Threatt, Alexandra; Matthews, Jeffrey (2024): Data for Pollinator seed mixes are phenologically dissimilar to prairie remnants. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-0185914_V1
This is the data set for the article entitled "Pollinator seed mixes are phenologically dissimilar to prairie remnants," a manuscript pending publication in Restoration Ecology. This represents the core phenology data of prairie remnant and pollinator seed mixes that were used for the main analyses. Note that additional data associated with the manuscript are intended to be published as a supplement in the journal.
keywords:
native plants; ecological restoration; tallgrass prairie; native plant materials
published: 2025-06-26
Zhang, Ruolin; Kontou, Eleftheria (2025): Data for Urban Electric Vehicle Infrastructure: Strategic Planning for Curbside Charging. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-8883290_V1
This dataset supports the analysis presented in the study on curbside electric vehicle (EV) charging infrastructure planning in San Francisco and the published paper titled "Urban electric vehicle infrastructure: Strategic planning for curbside charging." It includes spatial data layers and tabular data used to evaluate location suitability under multiple criteria, such as demand, accessibility, and environmental benefits. This dataset can be used to replicate the multi-criteria decision-making framework, perform additional spatial analyses, or inform policy decisions related to EV infrastructure siting in urban environments.
keywords:
Electric Vehicles; Curbside Charging Stations; Multi-Criteria Decision-Making; Suitability Analysis; Urban Infrastructure
published: 2024-07-29
Caetano Machado Lopes, Lorran; Chacko, George (2024): A Citation Graph from OpenAlex (Works). University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-7362697_V1
This dataset consists of a citation graph. It was constructed by downloading and parsing the Works section of the Open Alex catalog of the global research system. Open Alex (see citation below) contains detailed information about scholarly research, including articles, authors, journals, institutions, and their relationships. The data were downloaded on 2024-07-15. The dataset comprises two compressed (.xz) files. 1) filename: openalexID_integer_id_hasDOI.parquet.xz. The tabular data within contains three columns: openalex_id, integer_id, and hasDOI. Each row represents a record with the following data types: • openalex_id: A unique identifier from the Open Alex catalog. • integer_id: An integer representing the new identifier (assigned by the authors) • hasDOI: An integer (0 or 1) indicating whether the record has a DOI (0 for no, 1 for yes). 2) filename: citation_table.tsv.xz This edgelist of citations has two columns (no header) of integer values that represent citing and cited integer_id, respectively. Summary Features • Total Nodes (Documents): 256,997,006 • Total Edges (citations): 2,148,871,058 • Documents with DOIs: 163,495,446 • Edges between documents with DOIs: 1,936,722,541 The code used to generate these files can be found here: https://github.com/illinois-or-research-analytics/lorran_openalex/
keywords:
citation networks; Open Alex
published: 2024-11-15
Blanke, Steven; Ringling, Megan; Tan, Ivilyn; Oh, Seung (2024): Vacuolating cytotoxin A interactions with the host cell surface . University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-7490114_V1
This page contains the data for the manuscript "Vacuolating cytotoxin A interactions with the host cell surface". This manuscript is currently in prep.
keywords:
Steven R Blanke; Vacuolating cytotoxin A; VacA; Helicobacter pylori; protein binding; sphingomyelin; cell surface
published: 2024-11-13
Tang, Zhichu; Chen, Wenxiang; Yin, Kaijun; Busch, Robert; Hou, Hanyu; Lin, Oliver; Lyu, Zhiheng; Zhang, Cheng; Yang, Hong; Zuo, Jian-Min ; Chen, Qian (2024): Nanoscale Stacking Fault Engineering and Mapping in Spinel Oxides for Reversible Multivalent Ion Insertion. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-8188066_V1
These datasets are for the four-dimensional scanning transmission electron microscopy (4D-STEM) and electron energy loss spectroscopy (EELS) experiments for cathode nanoparticles at different states. The raw 4D-STEM experiment datasets were collected by TEM image & analysis software (FEI) and were saved as SER files. The raw 4D-STEM datasets of SER files can be opened and viewed in MATLAB using our analysis software package of imToolBox available at https://github.com/flysteven/imToolBox. The raw EELS datasets were collected by DigitalMicrograph software and were saved as DM4 files. The raw EELS datasets can be opened and viewed in DigitalMicrograph software or using our analysis codes available at https://github.com/chenlabUIUC/OrientedPhaseDomain. All the datasets are from the work "Nanoscale Stacking Fault Engineering and Mapping in Spinel Oxides for Reversible Multivalent Ion Insertion" (2024). The 4D-STEM experiment data include four example datasets for cathode nanoparticles collected at pristine and discharged states. Each dataset contains a stack of diffraction patterns collected at different probe positions scanned across the cathode nanoparticle. 1. Pristine untreated nanoparticle: "Pristine U-NP.ser" 2. Pristine 200ºC heated nanoparticle: "Pristine H200-NP.ser" 3. Untreated nanoparticle after first discharge in Zn-ion batteries: "Discharged U-NP.ser" 4. 200ºC heated nanoparticle after first discharge in Zn-ion batteries: "Discharged H200-NP.ser" The EELS experiment data includes six example datasets for cathode nanoparticles collected at different states (in "EELS datasets.zip") as described below. Each EELS dataset contains the zero-loss and core-loss EELS spectra collected at different probe positions scanned across the cathode nanoparticle. 1. Pristine untreated nanoparticle: "Pristine U-NP EELS.zip" 2. Pristine 200ºC heated nanoparticle: "Prisitne H200-NP EELS.zip" 3. Untreated nanoparticle after first discharge in Zn-ion batteries: "Discharged U-NP EELS.zip" 4. Untreated nanoparticle after first charge in Zn-ion batteries: "Charged U-NP EELS.zip" 5. 200ºC heated nanoparticle after first discharge in Zn-ion batteries: "Discharged H200-NP EELS.zip" 6. 200ºC heated nanoparticle after first charge in Zn-ion batteries: "Charged H200-NP EELS.zip" The details of the software package and codes that can be used to analyze the 4D-STEM datasets and EELS datasets are available at: https://github.com/chenlabUIUC/OrientedPhaseDomain. Once our paper is formally published, we will update the relationship of these datasets with our paper.
keywords:
4D-STEM; EELS; defects; strain; cathode; nanoparticle; energy storage
published: 2024-10-10
Zeiri, Offer; Hatzis, Katherine Marie; Gomez, Maurea; Cook, Emily A; Kincanon, Maegen; Murphy, Catherine (2024): Data for Self-Assembly of Hard Anions Around Cationic Gold Nanorods: Potential Structures for SERS. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-8630796_V1
keywords:
Gold nanorods, Surface enhanced Raman spectroscopy, SERS, Polyoxometalates
published: 2025-06-24
Ge, Jiankai; Weatherspoon, Howard; Peters, Baron (2025): 2025-GeWeatherspoonPeters-COFsPBM-codes. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-5767764_V1
This supporting information file contains codes related to pending publication Ge et al. Proc. Nat. Acad. Sci. USA, (revisions in review). The contents include a Mathematica code that solves the Laplace transformed equations and generates figures from the paper. A python code is included for generation of Figure 5 in the main text.
keywords:
Population balance model; Covalent organic framework; Nucleation; Growth;
published: 2024-09-16
Wu, Steven; Smith, Hannah (2024): Data on Controversies in Electric Vehicle Batteries. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-9365647_V1
This dataset describes an analysis of research documents about the debate between hydrogen fuel cells and lithium-ion batteries within the context of electric vehicles. To create this dataset, we first analyzed news articles on the topic of sustainable development. We searched for related science using keywords in Google Scholar. We then identified subtopics and selected one specific subtopic: electric vehicles. We started to identify positions and players about electric vehicles [1]. Within electric vehicles, we started searching in OpenAlex for a topic of reasonable size (about 300 documents) related to a scientific or technical debate. We narrowed to electric vehicles and batteries, then trained a cluster model [2] on OpenAlex’s keywords to develop some possible search queries, and chose one. Our final search query (May 7, 2024) returned 301 document in OpenAlex: Title & abstract includes: Electric Vehicle + Hydrogen + Battery filter is Lithium-ion Battery Management in Electric Vehicle We used a Python script and the Scopus API to find missing abstracts and DOIs [3]. To identify relevant documents, we used a combination of Abstractkr [4] and manual screening. As a starting point for Abstractkr [4], one person manually screened 200 documents by checking the abstracts for “hydrogen fuel cells” and “battery comparisons”. Then we used Abstractkr [4] to predict the relevance of the remaining documents based on the title, abstract, and keywords. The settings we used were single screening, ordered by most likely to be relevant, and 0 pilot size. We set a threshold of 0.6 for the predictions. After screening and predictions, 176 documents remained
keywords:
controversy mapping; sustainable development; evidence synthesis; OpenAlex; Abstrackr; Scopus; meta-analysis; electric vehicle; hydrogen fuel cells; battery
published: 2025-02-08
Anne, Lahari; Park, Minhyuk; Warnow, Tandy; Chacko, George (2025): Synthetic Networks For Benchmarking . University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-9805305_V1
The synthetic networks in this dataset were generated using the RECCS protocol developed by Anne et al. (2024). Briefly, the RECCS process is as follows. An input network and clustering (by any algorithm) is used to pass input parameters to a stochastic block model (SBM) generator. The output is then modified to improve fit to the input real world clusters after which outlier nodes are added using one of three different options. See Anne et al. (2024): in press Complex Networks and Applications XIII (preprint : arXiv:2408.13647). The networks in this dataset were generated using either version 1 or version 2 of the RECCS protocol followed by outlier strategy S1. The input networks to the process were (i) the Curated Exosome Network (CEN), Wedell et al. (2021), (ii) cit_hepph (https://snap.stanford.edu/), (iii) cit_patents (https://snap.stanford.edu/), and (iv) wiki_topcats (https://snap.stanford.edu/). Input Networks: The CEN can be downloaded from the Illinois Data Bank: https://databank.illinois.edu/datasets/IDB-0908742 -> cen_pipeline.tar.gz -> S1_cen_cleaned.tsv The synthetic file naming system should be interpreted as follows: a_b_c.tsv.gz where a - name of inspirational network, e.g., cit_hepph b - the resolution value used when clustering a with the Leiden algorithm optimizing the Constant Potts Model, e.g., 0.01 c- the RECCS option used to approximate edge count and connectivity in the real world network, e.g., v1 Thus, cit_hepph_0.01_v1.tsv indicates that this network was modeled on the cit_hepph network and RECCSv1 was used to match edge count and connectivity to a Leiden-CPM 0.01 clustering of cit_hepph. For SBM generation, we used the graph_tool software (P. Peixoto, Tiago 2014. The graph-tool python library. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1164194.v14) Additionally, this dataset contains synthetic networks generated for a replication experiment (repl_exp.tar.gz). The experiment aims to evaluate the consistency of RECCS-generated networks by producing multiple replicates under controlled conditions. These networks were generated using different configurations of RECCS, varying across two versions (v1 and v2), and applying the Connectivity Modifier (CM++, Ramavarapu et al. (2024)) pre-processing. Please note that the CM pipeline used for this experiment filters small clusters both before and after the CM treatment. Input Network : CEN Within repl_exp.tar.gz, the synthetic file naming system should be interpreted as follows: cen_<resolution><cm_status><reccs_version>sample<replicate_id>.tsv where: cen – Indicates the network was modeled on the Curated Exosome Network (CEN). resolution – The resolution parameter used in clustering the input network with Leiden-CPM (0.01). cm_status – Either cm (CM-treated input clustering) or no_cm (input clustering without CM treatment). reccs_version – The RECCS version used to generate the synthetic network (v1 or v2). replicate_id – The specific replicate (ranging from 0 to 2 for each configuration). For example: cen_0.01_cm_v1_sample_0.tsv – A synthetic network based on CEN with Leiden-CPM clustering at resolution 0.01, CM-treated input, and generated using RECCSv1 (first replicate). cen_0.01_no_cm_v2_sample_1.tsv – A synthetic network based on CEN with Leiden-CPM clustering at resolution 0.01, without CM treatment, and generated using RECCSv2 (second replicate). The ground truth clustering input to RECCS is contained in repl_exp_groundtruths.tar.gz.
keywords:
Community Detection; Synthetic Networks; Stochastic Block Model (SBM);
published: 2025-05-21
Punyasena, Surangi W.; Adaime, Marc-Elie; Jaramillo, Carlos (2025): Pollen of Podocarpus (Podocarpaceae) II: Airyscan confocal superresolution images. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-9559463_V1
This dataset includes a total of 16 images of 2 extant species of Podocarpus (Podocarpaceae) and 23 images of fossil specimens of the morphogenus Podocarpidites. The images were taken using a Zeiss LSM 880 microscope with Airyscan confocal superresolution at 630x magnification (63x/NA 1.4 oil DIC). The images are in the original CZI file format. They can be opened using Zeiss propriety software (Zen, Zen lite) or open microscopy software, such as ImageJ. More information on how to open CZI files can be found here: [https://www.zeiss.com/microscopy/us/products/software/zeiss-zen/czi-image-file-format.html] For Podocarpus (modern specimens): Each folder is labelled by genus and contain all images corresponding to that genus. Detailed information about the folders, files, and specimens can be found in the Excel file "METADATA_Podocarpus_extant.csv". This file includes metadata on: species, slide ID, collection, folder name file name and notes. Images are of pollen grains from slides in the Florida Museum of Natural History collections. For Podocarpidites (fossil specimens): Each image is named after the sample from which it was derived. Detailed information about the specimens can be found in the Excel file "METADATA_ Podocarpidites_fossil.csv". This file includes metadata: the fossil type (Taxon), the slide and sample name (Slide Info), the location of the sample locality (Country, Latitude, Longitude), the age of the sample (Min age, Max age), the location of the specimen on the sample slide (England Finder coordinates), and the image file name. Images are of fossil pollen from slides in Smithsonian Tropical Research Institute collections. Please cite this dataset and listed publications when using these images.
keywords:
optical superresolution microscopy; Zeiss Airyscan; CZI images; conifer; saccate pollen; Podocarpus; Podocarpidites
published: 2025-06-23
Kleiman, Diego; Feng, Jiangyan; Xue, Zhengyuan; Shukla, Diwakar (2025): Data for Fast and Accurate Prediction of Protein Dynamic Contact Maps from Single Sequences. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-3773897_V1
This repository contains data and model weights associated with the publication "Fast and Accurate Prediction of Protein Dynamic Contact Maps from Single Sequences". It includes the datasets used for training and evaluating a dynamic contact prediction model, ESMDynamic, as well as a script for conversion and usage.
keywords:
Computational biology; Structural biology; Molecular dynamics; Machine learning; Protein modeling; Bioinformatics; Biophysics; Artificial intelligence
published: 2024-08-06
Xing, Yuqing; Bae, Seokjin; Madhavan, Vidya (2024): Raw topographies for the study of magnetic field response of RbV3Sb5. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-0274244_V1
This is the raw topographies (without linear background subtraction) related to the publication: https://www.nature.com/articles/s41586-024-07519-5
published: 2025-04-02
Pastrana-Otero, Isamar; Godbole, Apurva R.; Kraft, Mary L. (2025): Data for Noninvasive and In Situ Identification of the Phenotypes and Differentiation Stages of Individual Living Cells Entrapped Within Hydrogels. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-5669414_V1
This dataset contains Raman spectra, each acquired from an individual, living, cell entrapped within a soft or stiff gelatin methacrylate hydrogel or from a cell-free region of the hydrogel sample. Spectra were acquired from the following cell types: Madin-Darby Canine Kidney cell (MDCK); Chinese hamster ovary cell (CHO-K1); transfected CHO-K1 cell that expressed the SNAP-tag and HaloTag reporter proteins fused to an organelle-specific protein (CHO-T); human monocyte-like cell (THP-1); inactive macrophage-like (M0-like); active anti-inflammatory macrophage-like (M2-like), pro/anti-inflammatory macrophage-like (M1/M2-like). These spectra are useful for identifying whether the hydrogel matrix obscures the Raman spectral signatures that are characteristic of each of these cell types.
keywords:
Raman spectroscopy; 3D cell culture; single-cell spectrum; hydrogel scaffold; collagen scaffold; macrophage spectra; macrophage differentiation; THP-1 line; noninvasive phenotype identification; vibrational spectroscopy
published: 2025-04-30
Davis, Mark (2025): Douglass et al. 2025 Ecology - Environmental DNA reveals the Salamander Mussel Simpsonaias ambigua alive in Illinois, USA, after a century in obscurity DATA. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-5667464_V1
This dataset represents the results of targeted eDNA assays via quantitative PCR for two imperiled freshwater species.
keywords:
Environmental DNA, Freshwater Mussel, Salamander, Conventional Surveys, Endangered Species, Habitat Use, Artificial Structures
planned publication date: 2025-08-05
Carrica, Lauren; Gulley, Joshua M. (2025): Data for Ontogeny of Catechol-O-Methyltransferase Expression in the Rat Prefrontal Cortex: Effects of Methamphetamine Exposure. University of Illinois Urbana-Champaign. https://doi.org/10.13012/B2IDB-7839940_V1
This dataset includes all data used in the manuscript by Carrica and Gulley titled, "Ontogeny of catechol-o-methyltransferase expression in the rat prefrontal cortex: effects of methamphetamine exposure"
keywords:
dopamine clearance; adolescence; drug exposure; prefrontal cortex