Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
85
datasets available to search
ShareScore release 0.9.0
Dataset results
85 results for “characterization method”
Geophysical data from: "A review of geophysical methods for soil structure characterization"
<p>The geophysical data presented herein was collected in the Soil Structure Observatory (see, Keller et. al. 2017) and were used to create Figures 4b, 5a, 5b, 9a and 9b for the manuscript entitled: "A review of geophysical methods for soil structure characterization" submitted to reviews of geophysics. The data set includes:<br> <br> GPR data collected from South to North in the bare soil of block C before and after compaction<br> GPR_800Mhz_BSbeforecompaction.DZW<br> GPR_800Mhz_BSbeforecompaction.DZT<br> GPR_800Mhz_BSaftercompaction.DZW<br> GPR_800Mhz_BSaftercompaction.DZT<br> <br> ERT data collected from South to North in the bare soil of block B before and after compaction<br> ERT_B2_14-03beforecompaction.bin<br> ERT_B2_14-04aftercompaction.bin<br> <br> Time-lapse ERT data collected in block A in September of 2017:<br> timelapseERT2017.zip<br> The date and time in the files names indicate the time in which the resistivimeter started collecting data plus two hours.<br> e.g. for 2017-09-11-18-01-41.bin, the first data point was collected at 14:01 on the 11th of September of 2017.<br> The first 464 data points correspond to bare soil collected from North to South<br> The following 464 data points correspond to grassy soil from South to North<br> <br> Meteorological data from 2017<br> meteodata_Reckenholz2017.xls<br> <br> Time domain reflectometry data from September of 2017 for block A (10, 20, 40 and 70cm depth). Two land covers (bare soil and grassy soil) and two compaction treatments (full compacted and non compacted) are included.<br> TDR_A1_Sept2017.xlsx</p> <p> </p> <p>Keller, T., Colombi, T., Ruiz, S., Manalili, M. P., Rek, J., Stadelmann, V., ... & Schymanski, S. (2017). Long-Term Soil Structure Observatory for Monitoring Post-Compaction Evolution of Soil Structure. <em>Vadose Zone Journal</em>, <em>16</em>(4).</p>
Development of a Standard Test Method for Characterization of Asphalt Modifiers and Aging-Related Degradation Using an Extensional Rheometer
<p>Corresponding data set for Tran-SET Project No. 17BLSU01. Abstract of the final report is stated below for reference:</p> <p>"An extensional deformation test method using a Sentmanat Extensional Rheometer (SER) fixture inside a Dynamic Shear Rheometer (DSR) is developed in this study to investigate the degradation of the polymer due to aging and to investigate the effect of modifier type. A relationship between different percentages of modifier and ductility of the modified binder is also investigated. The sample geometrics used in this study are 1 mm 0.72 mm and 3 mm 0.72 mm. A total of one hundred and sixty-two samples were tested. Three modifiers Styrene-Butadiene-Styrene (SBS), Polyphosphoric Acid (PPA) and latex were used. One PG 76-22, one PG 64-22 and one polymer-modified asphalt emulsion (PAME) were used. First peak elongation force, (F1) is the binders’ stiffness and Second peak elongation force, (F2) is the polymer characteristics. F2 is more visible comparatively at the higher temperature. In most cases, F2 reduces after Rolling Thin Film Oven (RTFO) and Pressure Aging Vessel (PAV) aging. To normalize the stiffness effect of F1 on F2, in this study F2/F1 was used to analyze aging susceptibility of modifiers. All the testing temperatures used in this study exhibited a reduction in F2/F1 due to RTFO aging and further reduction due to PAV aging. Therefore, through this study, it is recommended that this parameter can be used to determine aging susceptibility of polymer in a polymer-modified asphalt binder. F2 is only obtained from the SBS and latex modified binders and emulsions. Addition of PPA did not show any F2, making SBS the most effective modifier among SBS, PPA and latex. F2 has a linear correlation with the percent of the polymer in the PMAE, SBS modified PG 64-22, SBS and PPA modified PG 64-22 and latex modified PG 64-22 with R2 values equal to 0.9934, 0.9323, 0.9893 and 0.9535 respectively, indicating extensional deformation test with SER very promising. Ductility analyses using final angular strain values indicate that modifiers increase ductility significantly while aging reduces ductility. Additional research is required for testing ultra-violet (UV) aged sample, and a DSR-based SER test specification will be developed subsequently."</p>
Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator
<p>Dataset related to Huu-Hien Huynh, Vincent Delatour, Maxence Derbez-Morin, Qinde Liu, Amandine Boeuf, and Joëlle Vinh, (2022) Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator. Anal. Chem. 2022, 94, 10, 4146–4154.</p>
Data and Code Repository for Expanding non-target analysis methods to characterize the prenatal exposome
<p>Data and Code Repository for the following manuscript: Expanding non-target analysis methods to characterize the prenatal exposome. </p>
Data from: Characterization of binding kinetics and intracellular signaling of new psychoactive substances targeting cannabinoid receptor using transition-based reweighting method
Open the record for dataset details and reuse information.
A method for characterizing disease emergence curves from paired pathogen detection and serology data
Open the record for dataset details and reuse information.
Data from: Nanoindentation methods for viscoelastic characterization of stiff porous materials
Open the record for dataset details and reuse information.
Data for: Characterizing multi-criteria decision analysis, risk stratification, and hotspot analysis methods to optimise disease policymaking and evidence translation for medicines in low- and middle-income countries: A scoping review
Open the record for dataset details and reuse information.
Data from: What smells? Developing in-field methods to characterize the chemical composition of wild mammalian scent cues
Open the record for dataset details and reuse information.
FucoSan: Extraction of fucoidans from different brown algae species using different methods and their chemical and biological characterization
<p>This is a dataset extracted from the database of the Interreg project “FucoSan – Health from the sea” which includes information on the used algae species, the extraction of fucoidans as well as their chemical and pharmacological characterization.</p> <p>Macroalgae represent a vast source of renewable raw materials for research, development and application. An example of current high interest are fucoidans from brown algae. These fucose-containing sulfated polysaccharides exhibit a multitude of bioactivities offering attractive options for applications in medicine and cosmetics. The composition and chemical structure of fucoidans and thus their bioactivities may, however, largely vary depending on the algae species, extraction procedure and many other factors. Therefore, much research is still needed in the range from the algal source up to the targeted development of fucoidans optimized for respective applications. Since 2017, this is the topic of the Danish-German project Interreg project “FucoSan – health from the Sea” involving 11 partners with different expertise. Here, the current state of the fucoidan series produced and explored within the project is presented including information on the used algae species and batches, the extraction, purification and fractionation of the fucoidans as well as their chemical and pharmacological characterization. Based on their basic pharmacological activities, fucoidans are then selected and further tested in advanced experiments for specific applications in medicine and cosmetics.</p>
Data from: Linking genetic kinship and demographic analyses to characterize dispersal: methods and application to Blanding's turtle
Characterizing how frequently, and at what life stages and spatial scales, dispersal occurs can be difficult, especially for species with cryptic juvenile periods and long reproductive life spans. Using a combination of mark–recapture information, microsatellite genetic data, and demographic simulations, we characterize natal and breeding dispersal patterns in the long-lived, slow-maturing, and endangered Blanding's turtle (Emydoidea blandingii), focusing on nesting females. We captured and genotyped 310 individual Blanding's turtles (including 220 nesting females) in a central Wisconsin population from 2010 to 2013, with additional information on movements among 3 focal nesting areas within this population available from carapace-marking conducted from 2001 to 2009. Mark–recapture analyses indicated that dispersal among the 3 focal nesting areas was infrequent (<0.03 annual probability). Dyads of females with inferred first-order relationships were more likely to be found within the same nesting area than split between areas, and the proportion of related dyads declined with increasing distance among nesting areas. The observed distribution of related dyads for nesting females was consistent with a probability of natal dispersal at first breeding between nearby nesting areas of approximately 0.1 based on demographic simulations. Our simulation-based estimates of infrequent female dispersal were corroborated by significant spatial genetic autocorrelation among nesting females at scales of <500 m. Nevertheless, a lack of spatial genetic autocorrelation among non-nesting turtles (males and females) suggested extensive local connectivity, possibly mediated by male movements or long-distance movements made by females between terrestrial nesting areas and aquatic habitats. We show here that coupling genetic and demographic information with simulations of individual-based population models can be an effective approach for untangling the contributions of natal and breeding dispersal to spatial ecology.
Data from: Comparison of 454 pyrosequencing methods for characterizing the major histocompatibility complex of nonmodel species and the advantages of ultra deep coverage
Characterization and population genetic analysis of multilocus genes, such as those found in the major histocompatibility complex (MHC) is challenging in nonmodel vertebrates. The traditional method of extensive cloning and Sanger sequencing is costly and time-intensive and indirect methods of assessment often underestimate total variation. Here, we explored the suitability of 454 pyrosequencing for characterizing multilocus genes for use in population genetic studies. We compared two sample tagging protocols and two bioinformatic procedures for 454 sequencing through characterization of a 185-bp fragment of MHC DRB exon 2 in wolverines (Gulo gulo) and further compared the results with those from cloning and Sanger sequencing. We found 10 putative DRB alleles in the 88 individuals screened with between two and four alleles per individual, suggesting amplification of a duplicated DRB gene. In addition to the putative alleles, all individuals possessed an easily identifiable pseudogene. In our system, sequence variants with a frequency below 6% in an individual sample were usually artefacts. However, we found that sample preparation and data processing procedures can greatly affect variant frequencies in addition to the complexity of the multilocus system. Therefore, we recommend determining a per-amplicon-variant frequency threshold for each unique system. The extremely deep coverage obtained in our study (approximately 5000×) coupled with the semi-quantitative nature of pyrosequencing enabled us to assign all putative alleles to the two DRB loci, which is generally not possible using traditional methods. Our method of obtaining locus-specific MHC genotypes will enhance population genetic analyses and studies on disease susceptibility in nonmodel wildlife species.
FIGURE 2 in Monoecocestus (Cestoda: Anoplocephalidae) diversity in Sigmodontinae rodents characterized by morphology and molecular methods
FIGURE 2. Scanning electron micrographs of Monoecocestus threlkeldi: (a) scolex, lateral view; (b) acicular filitriches; (c) genital peduncle with everted cirrus, apical view; (d) genital peduncle, lateral view; (e) cirrus spined; (f) cirrus spines detail. Histological section of Monoecocestus sp.3: (g) full strobila; (h) cirrus sac and cirrus spined.
FIGURE 4 in Monoecocestus (Cestoda: Anoplocephalidae) diversity in Sigmodontinae rodents characterized by morphology and molecular methods
FIGURE 4. Phylogenetic tree of Monoecocestus spp. (Cestoda: Anoplocephalidae) based on concatenated rDNA (ITS1) and mtDNA (cox1). Phylogenetic tree inferred using Bayesian method. Maximum Likelihood bootstrap values of clades are listed first, followed by Bayesian Posterior Probabilities respectively, for clade frequencies exceeding 65%.
FIGURE 1 in Monoecocestus (Cestoda: Anoplocephalidae) diversity in Sigmodontinae rodents characterized by morphology and molecular methods
FIGURE 1. Morphological features of Monoecocestus threlkeldi: (a) scolex, (b) mature proglottids, (c) egg; Monoecocestus sp.1: (d) scolex, (e) mature proglottids, (f) egg; Monoecocestus sp.2: (g) scolex, (h) mature proglottids, (i) egg; Monoecocestus sp.3: (j) scolex, (k) mature proglottids, (l) egg.
FIGURE 3 in Monoecocestus (Cestoda: Anoplocephalidae) diversity in Sigmodontinae rodents characterized by morphology and molecular methods
FIGURE 3. Phylogenetic tree of Monoecocestus spp. (Cestoda: Anoplocephalidae) based on the rDNA (ITS1). Phylogenetic tree inferred using Bayesian method. Maximum Likelihood bootstrap values of clades are listed first, followed by Bayesian Posterior Probabilities respectively, for clade frequencies exceeding 65%.
Supplementary Figure S1 in Monoecocestus (Cestoda: Anoplocephalidae) diversity in Sigmodontinae rodents characterized by morphology and molecular methods
Supplementary Figure S1. Phylogenetic tree of Monoecocestus spp. (Cestoda: Anoplocephalidae) based on mtDNA (cox1). Phylogenetic tree inferred using Bayesian method. Maximum Likelihood bootstrap values of clades are listed first, followed by Bayesian Posterior Probabilities respectively, for clade frequencies exceeding 65%.
The 3'-RACE data (InPACT: A computational method for accurate characterization of intronic polyadenylation from RNA sequencing data)
Open the record for dataset details and reuse information.
Tractography derived quantitative estimates of tissue microstructure depend on streamline length: A characterization and method of adjustment.
<p>In respect of the brain imaging files upon which these analyses are based, three participants provided consent for their exemplar, pseudo-anonymised, data to be placed in the public domain. The example R code can be used to analyse these data.</p>
Facile synthesis of Cu2O nanorods in the presence of NaCl by SILAR method and its characterizations
<p>Cu<sub>2</sub>O nanorods have been deposited on soda-lime glass (SLG) substrates by the modified SILAR technique by varying the concentration of NaCl electrolyte into the pre-cursor complex solution. The structural, electrical, and optical properties of synthesized Cu<sub>2</sub>O nanorod films have been studied by a variety of characterization tools. Structural analyses by XRD confirmed the polycrystalline Cu<sub>2</sub>O phase with (111) preferential growth. Raman scattering spectroscopic measurements conducted at room temperature also showed characteristic peaks of the pure Cu<sub>2</sub>O phase. The surface resistivity of the Cu<sub>2</sub>O nanorod films decreased from 15,142 to 685 Ω.cm with the addition of NaCl from 0 to 4 mmol, and then exhibited an opposite trend with further addition of NaCl. The optical bandgap of the synthesized Cu<sub>2</sub>O nanorod films was observed as 1.88~2.36 eV, while the temperature-dependent activation energies of the Cu<sub>2</sub>O films were measured as about 0.14~0.21 eV. SEM morphologies demonstrated Cu<sub>2</sub>O nanorod as well as closely packed spherical grains with the alteration of NaCl concentration. The Cu<sub>2</sub>O phase of nanorods was found stable up to 230<i>℃</i><span><span> </span></span>corroborating the optical bandgap results of the same. The film fabricated in presence of 4 mmol of NaCl showed the lowest resistivity and activation energy as well comparatively uniform nanorod morphology. Our studies demonstrate that the nominal presence of NaCl electrolytes in the pre-cursor solutions has a significant impact on the physical properties of Cu<sub>2</sub>O nanorod films which could be beneficial in optoelectronic research.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.