Dataset Search

Results of RT-LAMP reactions for influenza A virus diagnostic development.

Root exudation is a key process for plant nutrient acquisition, but the controls on root exudation and its relationship to soil C and N processes in agroecosystems are unclear. We hypothesized that root exudation rates would be related to root morphological traits, N fertilization, and soil moisture. We also anticipated that root exudation would be correlated with bulk soil enzyme activity. Root exudation, root traits, and bulk soil extracellular enzyme activity were assessed in maize (Zea mays L.), soybean (Glycine max (L.) Merr.), biomass sorghum (Sorghum bicolor (L.) Moench), giant miscanthus (Miscanthus × giganteus), and switchgrass (Panicum virgatum L.). Measurements were taken in situ during two growing seasons with contrasting precipitation regimes, and N fertilization rate was varied in sorghum during one year. Specific root exudation (per unit root surface area) was negatively related to root diameter and was generally higher in annuals than perennials. Sorghum N fertilization did not affect root exudation rates, and soil moisture regime had no effect on annual root exudation rates within maize, sorghum, and miscanthus. Specific root exudation was negatively related to bulk soil C- and N-degrading soil enzyme activities. Intrinsic plant characteristics appeared more important than environmental variables in controlling in situ root exudation rates. The relationships between root diameter, root exudation, and soil C and N processes link root morphological traits to soil functions and demonstrate the potential tradeoffs among plant nutrient acquisition strategies in agroecosystems.

The data files are for the paper entitled: Long-lifetime spin excitations near domain walls in 1T-TaS2 to be published in PNAS. The data was obtained on a 300 mK custom designed Unisoku scanning tunneling microscope using the Nanonis module. All the data files have been named based on the Figure numbers that they represent.

Shared dataset consists of 16S sequencing data of microbial communities. Each community is composed of heterotrophic bacteria derived from one of two soil samples and the model algae Chlamydomonas reinhardtii. Each comunity was placed in a materially closed environment with an initial supply of carbon in the media and subjected to light-dark cycles. The closed microbial ecosystems (CES) survived via carbon cycling. Each CES was subjected to rounds of dilution, after which the community was sequenced (data provided here). The shared dataset allowed us to conclude that CES consistently self-assembled to cycle carbon (data not provided) via conserved metabolic capabilites (data not provided) dispite differences in taxonomic composition (data provided). --------------------------- Naming convention: [soil sample = A or B][CES replicate = 1,2,3, or 4]_[round number = 1,2,3,or 4]_[reverse read = R or forward read = F]_filt.fastq Example -- A1_r1_F_filt.fastq means soil sample A, CES replicate 1, end of round1, forward read

This dataset contains model code (including input data) to replicate the outcomes for "Assessing the Efficiency Implications of Renewable Fuel Policy Design in the United States". The model consists of: (1) The replication codes and data for the model. To run the model, using GAMS to run the "Models.gms" file.

The availability of economically marginal land for energy crops is identified using the Cropland Data Layer and other soil, wind, climate data resources. All data are recognized on a 30m spatial resolution across the continental United States.

This dataset is a snapshot of the presence and structure of entrepreneurship education in U.S. four-year colleges and universities in 2015, including co-curricular activities and related infrastructure. Public, private not-for-profit and for-profit institutions are included, as are specialized four-year institutions. The dataset provides insight into the presence of entrepreneurship education both within business units and in other units of college campuses. Entrepreneurship is defined broadly, to include small business management and related career-focused options.

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation.

To gather news articles from the web that discuss the Cochrane Review (DOI: 10.1002/14651858.CD006207.pub6), we retrieved articles on August 1, 2023 from used Altmetric.com's Altmetric Explorer. We selected all articles that were written in English, published in the United States, and had a publication date <b>on or after March 10, 2023</b> (according to the "Mention Date" from Altmetric.com). This date is significant as it is when Cochrane issued a statement (https://www.cochrane.org/news/statement-physical-interventions-interrupt-or-reduce-spread-respiratory-viruses-review) about the "misleading interpretation" of the Cochrane Review made by news articles. A previously published dataset for "Arguing about Controversial Science in the News: Does Epistemic Uncertainty Contribute to Information Disorder?" (DOI: 10.13012/B2IDB-4781172_V1) contains annotation of the news articles published before March 10, 2023. Our dataset annotates the news published on or after March 10, 2023. The Altmetric_data.csv describes the selected news articles with both data exported from Altmetric Explorer and data we manually added Data exported from Altmetric Explorer: - Publication date of the news article - Title of the news article - Source/publication venue of the news article - URL - Country Data we manually added: - Whether the article is accessible - The date we checked the article - The corresponding ID of the article in MAXQDA For each article from Altmetric.com, we first tried to use the Web Collector for MAXQDA to download the article from the website and imported it into MAXQDA (version 22.8.0). We manually extracted direct quotations from the articles using MAXQDA. We included surrounding words and sentences around direct quotations for context where needed. We manually added codes and code categories in MAXQDA to identify the individuals (chief editors of the Cochrane Review, government agency representatives, journalists, and other experts such as physicians) or organizations (government agencies, other organizations, and research publications) who were quoted. The MAXQDA_data.csv file contains excerpts from the news articles that contain the direct quotations we annotated. For each excerpt, we included the following information: - MAXQDA ID of the document from which the excerpt originates - The collection date and source of the document - The code we assigned to the excerpt - The code category - The excerpt itself

β‐Carotene is a natural pigment and health‐promoting metabolite, and has been widely used in the nutraceutical, feed, and cosmetic industries. Here, we engineered a GRAS yeast Saccharomyces cerevisiae to produce β‐carotene from xylose, the second most abundant and inedible sugar component of lignocellulose biomass. Specifically, a β‐carotene biosynthetic pathway containing crtYB, crtI, and crtE from Xanthophyllomyces dendrorhous was introduced into a xylose‐fermenting S. cerevisiae. The resulting strain produced β‐carotene from xylose at a titer threefold higher than from glucose. Interestingly, overexpression of tHMG1, which has been reported as a critical genetic perturbation to enhance metabolic fluxes in the mevalonate pathway and β‐carotene production in yeast when glucose is used, did not further improve the production of β‐carotene from xylose. Through fermentation profiling, metabolites analysis, and transcriptional studies, we found the advantages of using xylose as a carbon source, instead of glucose, for β‐carotene production to be a more respiratory feature of xylose consumption, a larger cytosolic acetyl‐CoA pool, and an upregulated expression level of rate‐limiting genes in the β‐carotene‐producing pathway, including ACS1 and HMG1. As a result, 772.8 mg/L of β‐carotene was obtained in a fed‐batch bioreactor culture with xylose feeding. Considering the inevitable large scale production of xylose when cellulosic biomass‐based bioeconomy is implemented, our results suggest xylose utilization is a promising strategy for overproduction of carotenoids and other isoprenoids in engineered S. cerevisiae.

Sugarcane is being enhanced as a bioenergy crop by engineering it to accumulate and store lipids along with polymeric sugars in vegetative tissues. However, there is no existing process that allows for processing this new crop to recover both lipid and cellulosic sugars from the oilcane bagasse. Therefore, a comprehensive investigation of two pretreatment methods—natural deep eutectic solvents (NADES) and chemical-free hydrothermal pretreatment (HT) was conducted to judge their suitability for recovering fermentable sugars, lipids, and lignin from bagasse. Two NADES, i.e., choline chloride: lactic acid (ChCl:LA) and betaine: lactic acid (BT:LA) were prepared using a 1:2 M ratio and were evaluated for pretreatment of oilcane bagasse at 10, 20, and 50 % (w/w) solids, followed by enzymatic hydrolysis at 10 % (w/w) solids. Notably, ChCl:LA NADES treatment at 10 % (w/w) solids at 140 °C for 2 h, solubilized 78.8 % of lignin and 80.4 % of hemicellulose and allowed 82.7 % enzymatic conversion of glucans to glucose. In contrast, HT pretreatment removed approximately 87.6 % of the hemicellulose and provided an enzymatic glucose yield of 69.7 %. Furthermore, ChCl:LA operated at 50 % solids loading the enriched lipids 2.6-fold (9.2 wt%) in recovered solids compared to HT (6.4 %) and BT:LA (5.1 %) pretreatment processes. NMR-HSQC and GPC analysis showed that ChCl:LA also cleaved the most lignin β–O–4 linkages and demonstrated lower molecular weight compared to HT. This study demonstrates that NADES pretreatment is an effective green processing method for recovering lipids, sugars, and lignin from bioenergy crops at high solid loading (50 % w/w) within the context of an integrated biorefinery.

An online knowledge, attitudes, and practices survey on ticks and tick-borne diseases was distributed to medical professionals in Illinois during summer 2020 to fall 2021. These are the raw data associated with that survey and the survey questions used. Age, gender, and county of practice have been removed for identifiability. We have added calculated values (columns 165 to end), including: the tick knowledge score, TBD knowledge score, and total knowledge score, which are the sum of the total number of correct answers in each category, and score percent, which are the proportion of correct answers in each category; region, which is determined from the county of practice; TBD relevant practice, which separates the practice variable into TBD primary, secondary, and non-responders; and several variables which group categories.

This dataset consists of all the files and codes that are part of the manuscript (main text and supplement) titled "Spin-selective tunneling from nanowires of the candidate topological Kondo insulator SmB6". For detailed information on the individual files refer to the specific readme files.

Datasets that accompany Beilke, Haulton, and O'Keefe 2022 publication (Title: Foliage-roosting eastern red bats select for features associated with management in a central hardwood forest; Journal: Forest Ecology and Management).

Datasets that accompany Beilke and O'Keefe 2022 publication (Title: Bats reduce insect density and defoliation in temperate forests: an exclusion experiment; Journal: Ecology).

This dataset supports the implementation described in the manuscript "Breaking the Barrier of Human-Annotated Training Data for Machine-Learning-Aided Biological Research Using Aerial Imagery." It comprises UAV aerial imagery used to execute the code available at https://github.com/pixelvar79/GAN-Flowering-Detection-paper. For detailed information on dataset usage and instructions for implementing the code to reproduce the study, please refer to the GitHub repository.

This dataset is the result of three crawls of the web performed in May 2018. The data contains raw crawl data and instrumentation captured by OpenWPM-Mobile, as well as analysis that identifies which scripts access mobile sensors, which ones perform some of browser fingerprinting, as well as clustering of scripts based on their intended use. The dataset is described in the included README.md file; more details about the methodology can be found in our ACM CCS'18 paper: Anupam Das, Gunes Acar, Nikita Borisov, Amogh Pradeep. The Web's Sixth Sense: A Study of Scripts Accessing Smartphone Sensors. In Proceedings of the 25th ACM Conference on Computer and Communications Security (CCS), Toronto, Canada, October 15–19, 2018. (Forthcoming)

This dataset contains the behavioral, metabolic, and capture data which is reported within the manuscript Data for Capture is predicted by behavior and size, not metabolism, in Muskellunge

Data at the lake summary and individual crayfish level that supports the manuscript Sawyer, E.K., Kreps, T. A., Lodge, D. M. and E.R. Larson. “Long-term declines in body size of the invasive rusty crayfish (Faxonius rusticus) in temperate lakes." Includes size measurements of 69,303 individual rusty crayfish (Faxonius rusticus) for 17 lakes of Vilas County, Wisconsin, United States collected between 1980 and 2020.

This dataset accompanies the research paper "Nine circles of elastic brittle fracture: A series of challenge problems to assess fracture models" by Kamarei, Zeng, Dolbow, and Lopez-Pamies, CMAME (2026). The dataset contains computational mesh files, figure data, and supporting materials for nine standardized challenge problems designed to assess fracture models in isotropic elastic brittle materials under quasi-static loading conditions. The nine challenge problems span the complete range of fracture nucleation and propagation mechanisms: strength nucleation (uniaxial tension, biaxial tension, torsion), Griffith nucleation (pure-shear, double cantilever beam, trousers), and strength-Griffith mediated nucleation (single edge notch, indentation, poker-chip). The dataset includes: High-quality mesh files for all nine challenge problems Figure data and results for both linear elastic (soda-lime glass) and non-linear elastic (PU elastomer) brittle materials

In the repository are example scripts that perform uncertainty injection and propagation to flux balance analysis with outputs for a small sample size (for demonstration purpose only). For proper analysis, user should download the scripts and run for a large sample size (e.g., 10,000 samples). If you use the scripts, please cite the following Metabolic Engineering article: “Quantifying the propagation of parametric uncertainty on flux balance analysis” (https://doi.org/10.1016/j.ymben.2021.10.012) There are two subdirectories: /uncFBA/uncBiom: injection of normally distributed noise to biomass precursor coeffcients and ATP maintenance (growth-associated ATP maintenance (GAM) and non-growth associated ATP maintenance (NGAM)) /uncFBA/uncRHS: departure from steady-state by adding noise drawn from normal distribution to the RHS terms of mass balance constraints

Downed woody debris census data for Trelease Woods collected in the summer of 2022. Dataset contains volume, biomass, decay class, and GPS coordinates for each downed woody debris piece.

Dataset of the standing dead trees at Trelease Woods in 2022. Dataset contains volume, biomass, decay class, and GPS coordinates for each standing dead tree.

The TrackDLO data release supports the paper, "TrackDLO: Tracking Deformable Linear Objects Under Occlusion with Motion Coherence," published in Robotics and Automation: Letters. The TrackDLO data release includes the raw image and depth data for tracking Deformable Linear Objects (DLOs) under tip occlusion, large-scale mid-section occlusion, and self-occlusion. The released data are Robot Operating System (ROS1) bag files containing raw color images and point clouds. The data were collected using a static Intel Realsense d-435 RGB-D camera while DLOs in the field of view of the camera were manipulated. The data can be used to benchmark the performance of future vision-only DLO tracking algorithms in several manipulation scenarios relevant to DLOs and to verify existing vision-only DLO tracking algorithms. Please see the RA-L paper, the code repository on GitHub, the conference presentation, and the supplementary demonstration video for more information.

This dataset contains best estimates of the particle size distribution and measurements of the radar reflectivity factor and total water content for instances where ground-based radar and airborne microphysical observations were considered collocated with each other.