Find research datasets worth reusing

opencc-by-4.0Oct 2021View details →

Fig. 2 in Comparative analysis of morphospace of Neotropical Sericini (Coleoptera: Scarabaeidae): disparity in the light of species diversity and activity patterns

Fig. 2 Illustration of potential trait correlation: A elytral length vs total body length, B maximum body width vs. vs total body length, C maximum body width vs. elytral length, D size of eyes (i.e., maximum ratio ocular diameter/minimum interocular distance) vs maxi-

opencc-by-4.0Aug 2024View details →

Predation activity data in organic, permaculture and conventional horticultural farms of Central Hungary

<p>This dataset has been produced from the PhD research of Alfréd Szilágyi supervised by Csaba Centeri and Eszter Kovács Tormáné. The study compared permaculture, organic and conventional farming systems regarding their ecosystem-service provision potential and sustainability. Multiple ecological indicators were measured in the field during the field study in 2020, and the basic datasets (soil test results; photo gallery of the studied farms with soil core sample; soil resistance and moisture; decomposition; earthworms; nematodes; soil surface fauna; pollinators; agrobiodiversity and habitat types) are uploaded in Zenodo separately to provide scientific data on permaculture systems. In this way, we hope to contribute to international efforts to evaluate the performance of agroecological agriculture alternatives. These publications also serve as supplements to the PhD thesis. For the sake of further usability of the datasets short description of the used methods is described. For further information please contact the authors.</p>

opencc-by-4.0Aug 2024View details →

The role of catchment characteristics, discharge, and active layer thaw on seasonal stream chemistry across ten permafrost catchments

<p>Data used for the paper: The role of catchment characteristics, discharge, and active layer thaw on seasonal stream chemistry across ten permafrost catchments. Contains water quality and discharge data. See paper for more details.</p>

opencc-by-nc-4.0Aug 2024View details →

DeDuCE: Deforestation and carbon emissions due to agriculture and forestry activities from 2001-2022

<h2>Overview</h2> <p>This dataset provides country-level estimates of agriculture and forestry-driven deforestation and associated carbon emissions for the period 2001-2022. A sub-national level attribution dataset is available for Brazil. Generated by the Deforestation Driver and Carbon Emission (DeDuCE) model, it amalgamates remotely sensed datasets with extensive agricultural statistics to estimate deforestation attributable to agricultural and forestry activities globally. Developed utilizing Google Earth Engine and Python, DeDuCE comprehensively covers over 9300 unique country-commodity footprints across <strong>179 countries and 184 commodities</strong> within the specified period, presenting an unmatched scope and granularity of data.</p> <h2>Documentation</h2> <p>The manuscript detailing the dataset is currently archived at EarthArXiV: <strong><em>Singh, C., & Persson, U. M. (2024). Global patterns of commodity-driven deforestation and associated carbon emissions</em></strong>. <a href="https://doi.org/10.31223/X5T69B" target="_blank" rel="noopener">https://doi.org/10.31223/X5T69B</a></p> <p>The insights from this dataset can also be viewed at: <strong><a href="https://www.deforestationfootprint.earth" target="_blank" rel="noopener">https://www.deforestationfootprint.earth</a></strong></p> <h2>Repository contents</h2> <p>The input and output/data generated by the model are archived here at <strong>Zenodo, </strong>and their description is available in <strong>'README (files in the directory).txt'</strong>.</p> <p>The columns of the (final) dataset '<em>DeDuCE_Deforestation_attribution_v1.0.1 (2001-2022).xlsx</em>' in the folder <em><strong>'Final Attribution Results'</strong></em> represent the following:</p> <ul> <li><strong>Continent/Country group: </strong>All countries are divided into 8 geographical regions</li> <li><strong>ISO: </strong>Three-letter country codes defined by ISO</li> <li><strong>Producer country: </strong>Country of deforestation</li> <li><strong>Year: </strong>Year of deforestation, ranges from 2001-2022 </li> <li><strong>Commodity group: </strong>All commodities are divided into 11 commodity groups</li> <li><strong>Commodity: </strong>Name of commodity aligning with FAOSTAT</li> <li><strong>Deforestation attribution, unamortized (ha): </strong>Annual deforestation estimates</li> <li><strong>Deforestation risk, amortized (ha): </strong>5-year amortised deforestation estimates</li> <li><strong>Deforestation emissions excl. peat drainage, unamortized (MtCO2): </strong>Annual estimates of carbon emissions (based on AGB, BGB, deadwood, litter, soil organic carbon and carbon stock of replacing commodity)</li> <li><strong>Deforestation emissions excl. peat drainage, amortized (MtCO2): </strong>5-year amortised carbon emission estimates, excluding carbon emissions from peatland drainage<strong> </strong></li> <li><strong>Peatland drainage emissions (MtCO2): </strong>Annual estimates of carbon emissions from peatland drainage<strong> </strong></li> <li><strong>Deforestation emissions incl. peat drainage, amortized (MtCO2): </strong>5-year amortised carbon emission estimates, including emissions from peatland drainage</li> <li><strong>Quality Index: </strong>Flagging deforestation estimates </li> </ul> <h2>Contact</h2> <p>If you have any questions, you can contact us at:        </p> <p>      Chandrakant Singh and U. Martin Persson   <br>      <em><strong><a href="mailto:chandrakant.singh@chalmers.se;martin.persson@chalmers.se">Email</a></strong>: chandrakant.singh@chalmers.se and martin.persson@chalmers.se   </em><br>      Physical Resource Theory, Department of Space, Earth & Environment,   <br>      Chalmers University of Technology, Gothenburg, Sweden</p>

Fig. 1 in Polybia fasticiosuscula (Hymenoptera: Vespidae) foraging activity patterns

Fig. 1. Typical Polybia fastidiosuscula foraging patterns. Means with the same letter at each evaluation time do not differ at 95% probability by the Tukey's test. Vertical bars represent the standard error of the mean (n = 7).

Fig. 5 in Effect of soil treatments for cottony cushion scale (Hemiptera: Monophlebidae) control on Nylanderia fulva (Hymenoptera: Formidicae) survival and trailing activity

Fig. 5. Correlations between the mean numbers of I. purchasi and N. fulva in pots treated with (A) CoreTect® (r = 0.88; n = 8), (B) Merit® 2F (r = 0.88; n = 8), and (C) control (untreated) (r = 0.60; n = 8).

Fig. 1 in Effect of soil treatments for cottony cushion scale (Hemiptera: Monophlebidae) control on Nylanderia fulva (Hymenoptera: Formidicae) survival and trailing activity

Fig. 1. Mean (n = 8) numbers of Icerya purchasi per pittosporum plant counted on 3 branches of each plant. Different letters indicate significantly different (P <0.05) means by repeated measures analysis of variance and Tukey HSD test (R Development Core Team 2012).

Fig. 4 in Effect of soil treatments for cottony cushion scale (Hemiptera: Monophlebidae) control on Nylanderia fulva (Hymenoptera: Formidicae) survival and trailing activity

Fig. 4. Mean numbers of Nylanderia fulva trails on the trunk of pittosporum plant. Different letters indicate significantly different (P <0.05) means by repeated measures analysis of variance and Tukey HSD test (R Core Team 2012).

Fig. 2 in Effect of soil treatments for cottony cushion scale (Hemiptera: Monophlebidae) control on Nylanderia fulva (Hymenoptera: Formidicae) survival and trailing activity

Fig. 2. Mean (n = 8) numbers of Nylanderia fulva counted from sausage samples placed near the base of the trunk of pittosporum plants. Different letters indicate significantly different (P <0.05) means by repeated measures analysis of variance and Tukey HSD test (R Core Team 2012).

opencc-by-4.0Dec 2023View details →

MAR2PROTECT Efficient Removal of Perfluorooctanoic acid (PFOA) using Fluorinated Ionic Liquids and Granular Activated Carbon DATASET

<p>Perfluoroalkylated and polyfluoroalkylated substances (PFAS) are persistent and bioaccumulative compounds in the environment and the human body. Their presence in high concentrations brings devastating consequences to health. Nowadays, there is an urgent need to develop efficient and sustainable processes that mitigate the damage caused by PFAS. This leads to improving the life quality of individuals. In the present work, for the first time, the extraction properties of PFOA with fluorinated ionic liquids (FILs) in aqueous media were evaluated. The most promising FIL is [P44414] [C4F9SO3] obtaining adsorption capacities up to 280 mg·g-1 in 72 h. Additionally, adsorption processes were carried out with granular activated carbon (GAC1240W) obtaining adsorption capacities up to 666 mg·g-1 best fitted with the pseudo-second order kinetic model with an equilibrium time of 48 h. Equilibrium  assays showed maximum uptake capacities around 500 mg.g-1, and a multilayer adsorption due to the best fit to Freundlich model. Both FILs and GAC1240W can open new paths in PFAS adsorption processes from aqueous solutions. Taking advantage of the properties of each one of them, new, more efficient, and sustainable processes can be optimized in the future.</p>

Fig 7 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 7. HCA dendrogram of 18 RS samples based on the NA inhibitory activity of compounds. Biennially cultivated RS (Group 1), perennially cultivated RS (Group 2), wild RS (Group 3) and plateau area RS (Group 4). https://doi.org/10.1371/journal.pone.0175751.g007

Fig 6 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 6. The relative NA inhibitory activity of baicalin, wogonin and wogonoside on HEK293Tcells. https://doi.org/10.1371/journal.pone.0175751.g006

Fig 3 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 3. Chromatogram of activity-integrated fingerprints of RS extracts. Chromatography (A) and total ion chromatography (B) of 26 compounds with NA inhibitory activity. Colored bar means the fraction collection purity> 98%. https://doi.org/10.1371/journal.pone.0175751.g003

Fig 2 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 2. Typical chromatogram. (A) RS extracts, (B) 9 standards mixture. Scutellarin (5), scutellarein (10), baicalin (11), chrysin-7-Oglucuronide (15), baicalein (19), wogonoside (22), wogonin (23), chrysin (24) and oroxylin A (25). https://doi.org/10.1371/journal.pone.0175751.g002

Fig 1 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 1. The principle of an activity integrated strategy method. The UPLC system with auto-fraction was used to separate, quantify collect and enrich the active compounds in fraction were performed by an. The fractions were used to test the bioactive analysis. https://doi.org/10.1371/journal.pone.0175751.g001

Fig 5 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 5. The cellular toxicity of baicalin, baicalein, wogonoside and wogonin. PLF and HIEC-6 cells were treated with indicated drugs with different concentrations as indicated for 24 hours and collected to evaluate cellular viability. https://doi.org/10.1371/journal.pone.0175751.g005

Fig 4 in An activity-integrated strategy of the identification, screening and determination of potential neuraminidase inhibitors from Radix Scutellariae

Fig 4. The NA inhibitory activity of compounds isolated from RS. The IC50 of Radix scutellariae extract scutellarin, scutellarein, baicalin, baicalein, wogonoside, wogonin, chrysin-7-O-glucuronideand chrysin by an NA inhibitory screening kit. https://doi.org/10.1371/journal.pone.0175751.g004

opencc-by-4.0Sep 2024View details →

Data for manuscript: The Conformational Space of the SARS-CoV-2 Main Protease Active Site Loops is Determined by Ligand Binding and Interprotomer Allostery

<div>The data is provided as a part of the manuscript "<strong>The Conformational Space of the SARS-CoV-2 Main Protease Active Site Loops is Determined by Ligand Binding and Interprotomer Allostery</strong>".  This repository includes an archive with folders:</div> <div> </div> <div><strong>md_data </strong></div> <div> <ul> <li>a directory with MD data for all simulation systems considered in the manuscript. Initial and final conformations are provided.</li> </ul> </div> <div> </div> <div><strong>fig_data</strong></div> <div> <ul> <li>a directory with the data underlying all the main text in the manuscript. </li> </ul> </div> <div> </div> <div>Videos S1-S3 are also included.</div>

opencc-by-4.0Jul 2024View details →

Data described in the article "Nitrogen-Containing Flavonoids─Preparation and Biological Activity"

<p>The dataset includes supplementary data, i.e. the results of optimization of Ullmann reaction, cellular antioxidant and anti-inflammatory activity, cytotoxicity, antibacterial activity, and molecular docking, <sup>1</sup>H, <sup>13</sup>C{<sup>1</sup>H} NMR data, HPLC, and HRMS analyses  of the study titled "Nitrogen-Containing Flavonoids─Preparation and Biological Activity" available here: <a href="https://doi.org/10.1021/acsomega.4c04627">https://doi.org/10.1021/acsomega.4c04627</a></p>