Find research datasets worth reusing

opencc-by-4.0Dec 2022View details →

Table 1 in Phytochemical characterization, and antioxidant and antibacterial activities of the hydroethanolic extract of Anadenanthera peregrina stem bark

<p><b>Table 1.</b> Phytochemical prospecting of the main secondary metabolite groups of the hydroethanolic extract of <i>A. peregrina</i> stem bark.</p><table><tbody><tr><th><b>Secondary metabolite</b></th><th><b>Hydroethanolic extract of A. peregrina</b></th></tr><tr><th><b>Cardiac glycosides</b></th></tr></tbody><tbody><tr><th>Kedd reagent test</th><td>++</td></tr><tr><th>Keller–Kiliani reagent test</th><td>++</td></tr><tr><th>Baljet reagent test</th><td>-</td></tr><tr><th>Raymond–Marthoud reagent test</th><td>+++</td></tr><tr><th><b>Alkaloids</b></th></tr><tr><th>Libermann–Bouchardat reagent test</th><td>-</td></tr><tr><th>Wagner reagent test</th><td>-</td></tr><tr><th>Mayer’s reagent test</th><td>-</td></tr><tr><th><b>Organic acids</b></th></tr><tr><th>Pascová reagent test</th><td>++</td></tr><tr><th><b>Reducing sugars</b></th></tr><tr><th>Fehling reagent test</th><td>++</td></tr><tr><th><b>Non-reducing sugars</b></th></tr><tr><th>Fehling + HCl test</th><td>-</td></tr><tr><th><b>Coumarins</b></th></tr><tr><th>UV light 254 and 365 nm</th><td>+</td></tr><tr><th><b>Saponins</b></th></tr><tr><th>Foamy</th><td>-</td></tr><tr><th>Haemolytic</th><td>+++</td></tr><tr><th><b>Polysaccharides</b></th></tr><tr><th>Reactive lugol</th><td>-</td></tr><tr><th><b>Phenols</b></th></tr><tr><th>FeCl 3 <b>Tannins</b></th><td>+++</td></tr><tr><th>FeCl3 <b>Flavonoids</b></th><td>Gr</td></tr><tr><th>Pb(C2 H 3O2)2</th><td>++</td></tr><tr><th><b>Purines</b></th><td><b>-</b></td></tr><tr><th><b>Catechins</b></th><td>+++</td></tr><tr><th><b>Benzoquinone derivatives</b></th><td>+++</td></tr><tr><th><b>Depsids and depsidones</b></th><td>+++</td></tr><tr><th><b>Steroids and triterpenoids</b></th><td><b>-</b></td></tr><tr><th><b>Sesquiterpenolactones</b></th><td>-</td></tr></tbody></table>

MyoD1 localization at the nuclear periphery is mediated by association of WFS1 with active enhancers - Image Dataset

<p>The set of raw images used in this study published on Nature Communications:</p> <p><a href="https://www.nature.com/articles/s41467-025-57758-x" target="_blank" rel="noopener">https://www.nature.com/articles/s41467-025-57758-x</a></p> <p>are available as 4 subsets below:</p> <p><a href="https://osf.io/w5n43/" target="_blank" rel="noopener">https://osf.io/w5n43/</a></p> <p><a href="https://osf.io/bfxdw/" target="_blank" rel="noopener">https://osf.io/bfxdw/</a></p> <div><a href="https://osf.io/rkguq/" target="_blank" rel="noopener">https://osf.io/rkguq/</a></div> <div> </div> <div><a href="https://osf.io/q6b4j/" target="_blank" rel="noopener">https://osf.io/q6b4j/</a> <div> </div> <div>The reason of this Zenodo entry is to combine these subsets into a single DOI link.</div> <div>The total size adds up to 200GB and it is not possible to host such a large dataset on Zenodo, and it is only possible as maximum of 50GB pieces on Open Science Framework.</div> <div> </div> <div>Summary of the study:</div> <div>Spatial organization of the mammalian genome influences gene expression and cell identity. While association of genes with the nuclear periphery is commonly linked to transcriptional repression, also active, expressed genes can localize at the nuclear periphery. The transcriptionally active MyoD1 gene, a master regulator of myogenesis, exhibits peripheral localization in proliferating myoblasts, yet the underlying mechanisms remain elusive. Using a newly generated reporter cell line, we demonstrate here that peripheral association of the MyoD1 locus is independent of mechanisms involved in heterochromatin anchoring. We identify a set of nuclear envelope transmembrane proteins, particularly WFS1, that actively tether MyoD1 to the nuclear periphery. WFS1 primarily associates with active distal enhancer elements upstream of MyoD1, and with a subset of enhancers enriched in active histone marks genome-wide, which are linked to expressed myogenic genes. Overall, our data identify a novel mechanism involved in tethering active genes to the nuclear periphery.</div> <div> </div> <div>This research was funded in whole or in part by the Austrian Science Fund (FWF) [P29713-B28, P32512-B and P36503-B] to Roland Foisner and a doctorate program funded by the Austrian Science Fund (FWF) [W1261-B28].</div> <div> </div> </div>

The role of chemical properties of the material deposited in nests of white stork in shaping enzymatic activity and fungal diversity - dataset

<p>Dataset to paper: Błońska E., Jankowiak R., Lasota J., Krzemińska N., Zbyryt A., Ciach M. 2024. The role of chemical properties of the material deposited in nests of white stork in shaping enzymatic activity and fungal diversity. Environmental Science and Pollution Research 31, 2: 2583-2594. https://doi.org/10.1007/s11356-023-31383-x</p> <p>This study was financially supported by the National Science Centre, Poland (grant no. 2021/41/B/NZ8/03456).</p>

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

Neutron activation analysis data of pottery from Pachacamac and other sites in the Lurín Valley, Peru

<p>Neutron activation analysis data of pottery from Pachacamac and other sites in the Lurín Valley, Peru</p>

Dataset Questionnaire Social Media Marketing Activities, Brand Loyalty, Brand Trust, Brand Equity, and Industry Fashion In Indonesia

<p>The following dataset is a dataset from a study that investigated Social Media Marketing Activities, Brand Loyalty, Brand Trust, and, Brand Equity in the context of fashion industry in Indonesia.</p>

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

Neutron activation analysis data of pottery, clay, obsidian, and andesite from multiple sites in Argentina

<p>Neutron activation analysis data of pottery, clay, obsidian, and andesite from multiple sites in Argentina and Chile</p> <p> </p>

opencc-by-4.0Feb 2020View details →

Table 2 in Phytotoxic activity of extracts obtained from cagaita (Eugenia dysenterica DC. - Myrtaceae) on the growth of black-jack (Bidens pilosa L.)

<p>Table 2. Effect of different leaf and stem bark extracts of <i>Eugenia dysenterica</i> DC. on the germination speed index (GSI) of <i>Bidens pilosa</i> L. seeds.</p><table><tbody><tr><th><b>Concentration (<b>mgL-</b> 1<b>)</b></b></th><th><b>LAE</b></th><th><b>LEE</b></th><th><b>LHE 70:30</b></th><th><b>LHE 50:50</b></th><th><b>SAE</b></th><th><b>SEE</b></th><th><b>SHE 70:30</b></th><th><b>SHE 50:50</b></th></tr></tbody><tbody><tr><th>0</th><td>18.20 A</td><td>18.20 A</td><td>18.20 A</td><td>18.20 A</td><td>18.20 A</td><td>18.20 A</td><td>18.20 A</td><td>18.20 A</td></tr><tr><th>250</th><td>15.10 B</td><td>13.60 B</td><td>9.95 B</td><td>7.30 B</td><td>10.60 B</td><td>13.30 B</td><td>12.90 B</td><td>14.20 B</td></tr><tr><th>500</th><td>19.61 A</td><td>12.20 B</td><td>8.18 B</td><td>9.60 B</td><td>9.65 B</td><td>12.20 B</td><td>8.41 C</td><td>9.79 C</td></tr><tr><th>1000</th><td>11.75 C</td><td>7.70 C</td><td>7.61 B</td><td>9.94 B</td><td>9.40 B</td><td>8.04 C</td><td>8.10 C</td><td>9.68 C</td></tr></tbody></table><p>Means followed by the same letter in the column do not differ from each other by the Tukey test at 5% probability. Leaf Aqueous Extract (LAE), Leaf Ethanolic Extract (LEE), Leaf Hydroalcoholic Extract 70:30 (LHE 70:30), Leaf Hydroalcoholic Extract 50:50 (LHE 50:50), Stem aqueous extract (SAE), Stem ethanolic extract (SEE), Stem hydroalcoholic extract 70:30 (SHE 70:30), and Stem hydroalcoholic extract 50:50 (SHE 50:50).</p>

opencc-by-4.0Feb 2020View details →

Table 1 in Phytotoxic activity of extracts obtained from cagaita (Eugenia dysenterica DC. - Myrtaceae) on the growth of black-jack (Bidens pilosa L.)

<p><b>Table 1</b>. Effect of different leaf and stem bark extracts of <i>Eugenia dysenterica</i> DC. on the germination percentage (G%) of <i>Bidens pilosa</i> L. seeds.</p><table><tbody><tr><th><b>Concentration (<b>mgL-</b> 1<b>)</b></b></th><th><b>LAE</b></th><th><b>LEE</b></th><th><b>LHE 70:30</b></th><th><b>LHE 50:50</b></th><th><b>SAE</b></th><th><b>SEE</b></th><th><b>SHE 70:30</b></th><th><b>SHE 50:50</b></th></tr></tbody><tbody><tr><th>0</th><td>64.00 A</td><td>64.00 A</td><td>64.00 A</td><td>64.00 A</td><td>64.00 A</td><td>64.00 A</td><td>64.00 A</td><td>64.00 A</td></tr><tr><th>250</th><td>59.84 A</td><td>59.14 A</td><td>60.33 A</td><td>59.35 A</td><td>59.18 A</td><td>58.81 A</td><td>58.16 A</td><td>59.11 A</td></tr><tr><th>500</th><td>57.48 A</td><td>59.76 A</td><td>41.56 B</td><td>42.00 B</td><td>57.00 A</td><td>57.25 A</td><td>48.16 B</td><td>42.48 B</td></tr><tr><th>1000</th><td>58.75 A</td><td>57.70 A</td><td>40.18 B</td><td>41.14 B</td><td>59.40 A</td><td>58.14 A</td><td>42.12 B</td><td>41.18 B</td></tr></tbody></table><p>Means followed by the same letter in the column do not differ from each other by the Tukey test at 5% probability. Leaf Aqueous Extract (LAE), Leaf Ethanolic Extract (LEE), Leaf Hydroalcoholic Extract 70:30 (LHE 70:30), Leaf Hydroalcoholic Extract 50:50 (LHE 50:50), Stem aqueous extract (SAE), Stem ethanolic extract (SEE), Stem hydroalcoholic extract 70:30 (SHE 70:30), and Stem hydroalcoholic extract 50:50 (SHE 50:50).</p>

Resources for "BMF CP 93: Characteristics of people likely to reduce outdoor activities due to wildfire smoke"

<p>The current study is conducted to examine the following research questions:</p> <ul> <li>Who were people more likely to reduce outdoor activities during the smoke event in the summer of 2018 in the Boise Metropolitan Area in Idaho?</li> <li>Who were people having more days with reduced outdoor activities during the smoke event in the summer of 2018 in the Boise Metropolitan Area in Idaho?</li> </ul>

MFB Liposome active learning

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Appendix Figures B.1–B.7 from the article 'Core Prominence as a Signature of Restarted Jet Activity in the LOFAR Radio-Galaxy Population' (Accepted for publication in the journal Astronomy & Astrophysics on August 23, 2024)

<p><strong>Figure captions:</strong></p> <p> </p> <p><strong>Figs. B.1–B.5.</strong> Images of 69 candidate restarted galaxies selected based on high radio $\mathrm{CP_{1400}}$ combined with low SB of extended emission, a steep spectrum of the core, and USS extended emission coupled with a bright core and summarised in Tables A.1 and A.2. Radio contours from VLA FIRST maps (white, $5^{\prime\prime}$), LOFAR high-resolution maps (black, $6^{\prime\prime}$), and NVSS maps (purple, $45^{\prime\prime}$) are overlaid on the LOFAR low-resolution resolution maps (orange, $20^{\prime\prime}$). The contouring of all the maps is made at $\,\sigma_\mathrm{local}\times(-3,3,5,10,20,30,40,50,100,150,200)$ levels, with $\sigma_\mathrm{local}$ representing the local RMS noise of the corresponding maps. The host galaxy position is marked with a yellow cross.</p> <p> </p> <p><strong>Figs. B.6–B.7. </strong>Images of sources excluded from the sample of restarted candidates following the criteria discussed in Sect. 3.1, Sect. 3.2 and Sect. 3.3 and summarised in Tables A.3 and A.4. Radio contours from VLA FIRST maps (white, $5^{\prime\prime}$), LOFAR high-resolution maps (black, $6^{\prime\prime}$), and NVSS maps (purple, $45^{\prime\prime}$) are overlaid on the LOFAR low-resolution resolution maps (orange, $20^{\prime\prime}$). The contouring of all the maps is made at $\,\sigma_\mathrm{local}\times(-3,3,5,10,20,30,40,50,100,150,200)$ levels, with $\sigma_\mathrm{local}$ representing the local RMS noise of the corresponding maps. The host galaxy position is marked with a yellow cross.</p> <p> </p>

Time series transcriptomes resolve metabolic pathways underlying crocin's anti-cancer activity | Dataset: sequencing reads (2,6,12,24 hr crocin treatments)

<p><span>Natural products like saffron show promise in treating hepatocellular carcinoma (HCC), but their mechanisms remain unclear. Here, we used time-series transcriptomics to elucidate crocin's anti-cancer mechanisms in HCC cells. We treated HepG2 cells with 1 and 2 mM crocin for 2, 6, 12, and 24 hours and analyzed transcriptomic profiles at each timepoint. The strongest transcriptional response occurred at 2 hours with 1 mM crocin, with diminishing effects at later timepoints. We observed upregulation of metabolic-, adhesion-, and endocytosis-related genes across all timepoints. Pathway analysis revealed activation of DNA damage checkpoints and senescence while proliferation pathways were suppressed. Notably, 52 genes involved in non-alcoholic fatty liver disease were downregulated at 24 hours (FDR p = 8 × 10⁻⁸), suggesting reversal of carcinogenic pathways. Strikingly, crocin consistently downregulated spliceosomal machinery genes across all timepoints while upregulating senescence and autophagy pathways. This spliceosome targeting represents a clinically relevant mechanism, as aberrant splicing drives oncogenesis in more than 90% of cancers. The transcription factor PAX5 was significantly upregulated while oncogenic ELK1 targets were downregulated. Our findings show that crocin treatment is accompanied by HCC cell senescence induction through coordinated spliceosome disruption and metabolic reprogramming, providing novel therapeutic targets for hepatocellular carcinoma.</span></p> <p><strong><span>Keywords: </span></strong><span>Hepatocellular carcinoma (HCC), crocin, transcriptomics, spliceosome, senescence, natural anti-cancer compounds</span></p>

MD Data for "A non-canonical mechanism of GPCR activation"

<p>Molecular dynamics simualtion data generated for "A non-canonical mechanism of GPCR activation". </p>

The Regulation of Microglia Activity and the Production of IL-1α and IL-6 in the Degenerated Retina by Mesenchymal Stem Cells

<p><span>Activation of immune response and production of proinflammatory factors plays an important role in the development and progression of retinal degenerative diseases (RDD). For this reason, focusing on immunomodulation is potential option for the efficient ophthalmological therapy. Mesenchymal stem cells (MSCs) have been study in the treatment of RDD mainly due to their regenerative and neuroprotective actions. Nevertheless, MSCs also possess several immunomodulatory properties. Our study shows that NaIO<sub>3</sub>-induced degeneration increased <em>in vitro</em> and <em>in vivo</em> expression of genes for Interleukin (IL)-1α and IL-6 in the mouse retinal tissue. In addition, intraperitoneal application of NaIO<sub>3</sub> increased expression of gene for Iba-1 and infiltration of CD45<sup>+</sup>CD11b<sup>+</sup> cells into the retina. CD45<sup>+</sup> population was also responsible for the production of IL-1α while IL-6 was produced by CD45<sup>-</sup> cells. Cocultivation of degenerated retina in the presence of MSCs decreased the expression and production of both studied cytokines and expression of gene for Iba-1 in the retinal tissue. On contrary, it was observed that MSCs treated with supernatant from degenerated retina increased the expression of genes for cyclooxygenase-2, transforming growth factor-β, programmed-death ligand 1 and nerve growth factor. These results show that MSCs are able to regulate immune reaction in the degenerated retinal environment.</span></p>

Exploring ultraweak photon emissions as optical markers of brain activity - Dataset and statistical models

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RBD24 - Risk Activities Dataset 2024

<h1>Introduction</h1> <p>This repository contains a selection of behavioral datasets collected using soluble agents and labeled using realistic threat simulation and IDS rules. The collected datasets are anonymized and aggregated using time window representations. The dataset generation pipeline preprocesses the application logs from the corporate network, structures them according to entities and users inventory, and labels them based on the IDS and phishing simulation appliances. </p> <p>This repository is associated with the article<strong> "RBD24: A labelled dataset with risk activities using log applications data" </strong> published in the journal <em>Computers & Security</em>. For more information go to <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.cose.2024.104290" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.cose.2024.104290</span></span></a></p> <h2> </h2> <p> </p> <h1>Summary of the Datasets </h1> <p>The RBD24 dataset comprises various risk activities collected from real entities and users over a period of 15 days, with the samples segmented by Desktop (DE) and Smartphone (SM) devices.</p> <table> <tbody> <tr> <td><strong>DatasetId</strong></td> <td><strong>Entity </strong></td> <td><strong>Observed Behaviour</strong></td> <td><strong>Groundtruth</strong></td> <td><strong>Sample Shape</strong></td> </tr> <tr> <td>Crypto_desktop.parquet</td> <td>DE</td> <td>Miner Checking</td> <td>IDS</td> <td>0: 738/161202, 1: 11/1343</td> </tr> <tr> <td>Crypto_smarphone.parquet</td> <td>SM</td> <td>Miner Checking</td> <td>IDS</td> <td>0: 613/180021, 1: 4/956</td> </tr> <tr> <td>OutFlash_desktop.parquet</td> <td>DE</td> <td>Outdated software components </td> <td>IDS</td> <td>0: 738/161202, 1: 56/10820</td> </tr> <tr> <td>OutFlash_smartphone.parquet</td> <td>SM</td> <td>Outdated software components </td> <td>IDS</td> <td>0: 613/180021, 1: 22/6639</td> </tr> <tr> <td>OutTLS_desktop.parquet</td> <td>DE</td> <td>Outdated TLS protocol</td> <td>IDS</td> <td>0: 738/161202, 1: 18/2458</td> </tr> <tr> <td>OutTLS_smartphone.parquet</td> <td>SM</td> <td>Outdated TLS protocol</td> <td>IDS</td> <td>0: 613/180021, 1: 11/2930</td> </tr> <tr> <td>P2P_desktop.parquet</td> <td>DE</td> <td>P2P Activity</td> <td>IDS</td> <td>0: 738/161202, 1: 177/35892</td> </tr> <tr> <td>P2P_smartphone.parquet</td> <td>SM</td> <td>P2P Activity</td> <td>IDS</td> <td>0: 613/180021, 1: 94/21688</td> </tr> <tr> <td>NonEnc_desktop.parquet</td> <td>DE</td> <td>Non-encrypted password</td> <td>IDS</td> <td>0: 738/161202, 1: 291/59943</td> </tr> <tr> <td>NonEnc_smaprthone.parquet</td> <td>SM</td> <td>Non-encrypted password</td> <td>IDS</td> <td>0: 613/180021, 1: 167/41434</td> </tr> <tr> <td>Phishing_desktop.parquet</td> <td>DE</td> <td>Phishing email</td> <td> <p>Experimental Campaign</p> </td> <td>0: 98/13864, 1: 19/3072</td> </tr> <tr> <td>Phishing_smartphone.parquet</td> <td>SM</td> <td>Phishing email</td> <td>Experimental Campaign</td> <td>0: 117/34006, 1: 26/8968</td> </tr> </tbody> </table> <p> </p> <h1> Methodology  </h1> <p>To collect the dataset, we have deployed multiple agents and soluble agents within an infrastructure with <br>more than 3k entities, comprising laptops, workstations, and smartphone devices. The methods to build <br>ground truth are as follows:</p> <p>- Simulator: We launch different realistic phishing campaigns, aiming to expose user credentials or defeat access to a service.<br>- IDS: We deploy an IDS to collect various alerts associated with behavioral anomalies, such as cryptomining or peer-to-peer traffic.</p> <p>For each user exposed to the behaviors stated in the summary table, different TW is computed, aggregating <br>user behavior within a fixed time interval. This TW serves as the basis for generating various supervised <br>and unsupervised methods.</p> <h2>Sample Representation</h2> <p>The time windows (TW) are a data representation based on aggregated logs from multimodal sources between two <br>timestamps. In this study, logs from HTTP, DNS, SSL, and SMTP are taken into consideration, allowing the <br>construction of rich behavioral profiles. The indicators described in the TE are a set of manually curated <br>interpretable features designed to describe device-level properties within the specified time frame. The most <br>influential features are described below. </p> <ul> <li>User:** A unique hash value that identifies a user.</li> <li>Timestamp:** The timestamp of the windows.</li> <li>Features</li> <li>Label:  1 if the user exhibits compromised behavior, 0 otherwise. -1 indicates that it is a TW with an unknown label.</li> </ul> <p> </p> <h2>Dataset Format</h2> <p>Parquet format uses a columnar storage format, which enhances efficiency and compression, making it suitable for large datasets and complex analytical tasks. It has support across various tools and languages, including Python. Parquet can be used with pandas library in Python, allowing pandas to read and write Parquet files through the `pyarrow` or `fastparquet` libraries. Its efficient data retrieval and fast query execution improve performance over other formats. Compared to row-based storage formats such as CSV, Parquet's columnar storage greatly reduces read times and storage costs for large datasets. Although binary formats like HDF5 are effective for specific use cases, Parquet provides broader compatibility and optimization.  The provided datasets use the Parquet format. Here’s an example of how to retrieve data using pandas, ensure you have the  fastparquet library installed:</p> <p>```<code>python</code><br><code>import pandas as pd</code></p> <p><code># Reading a Parquet file</code><br><code>df = pd.read_parquet(</code><br><code>  'path_to_your_file.parquet', </code><br><code>  engine='fastparquet'</code><br><code>  ) </code></p> <p>```</p>

Active larva of ?Selasia sp. from India preying on the snail

<p>Active larva of ?Selasia sp. (Coleoptera: Elateridae: Agrypninae: Drilini) from India preying on the snail</p>

opencc-by-4.0May 2024View details →

Supplementary Materials S1-S4 to Leipe et al., 2024. Human activities, early farming and natural environment in the north-western Kanto Plain (Central Japan) during the Final Jomon–Early Kofun period (990 cal BCE–330 cal CE) inferred from palynological and archaeobotanical records

<p>This dataset represents the Supplementary Materials S1-S4 to Leipe et al. (2024), <em>QEH</em> 2, 100030.</p> <p>Leipe et al., 2024. Human activities, early farming and natural environment in the north-western Kanto Plain (Central Japan) during the Final Jomon–Early Kofun period (990 cal BCE–330 cal CE) inferred from palynological and archaeobotanical records. <em>Quaternary Environments and Humans</em> 2, 100030 (doi: <a href="https://doi.org/10.1016/j.qeh.2024.100030">https://doi.org/10.1016/j.qeh.2024.100030</a>).</p> <p><strong>Supplementary Material S1</strong>: Pollen and non-pollen palynomorph records of a section (490.5-668.5 cm depth) of the MJ20 sediment core from Morinji Marsh, Tatebayashi City, Gunma Prefecture, Kanto region, Central Japan.</p> <p><strong>Supplementary Material S2</strong>. Sample-specific total counts of macrobotanical (seeds and fruits) and fungal remains and floated litres of sediment samples from ash pits (Yayoi period) and hearths (Kofun period) of the Ikegami archaeological site, Kumagaya City, Saitama Prefecture, Kanto region, Central Japan.</p> <p><strong>Supplementary Material S3</strong>. Photographs of charred remains of<em> Juglans ailantifolia</em> and <em>Aesculus turbinata</em> from the Middle Yayoi period ash pit samples at the Ikegami archaeological site, Kumagaya City, Saitama Prefecture, Kanto region, Central Japan.</p> <p><strong>Supplementary Material S4</strong>. Description of the As-B tephra in the MJ20 sediment core from Morinji Marsh, Tatebayashi City, Gunma Prefecture, Kanto region, Central Japan.</p>

opencc-by-4.0Mar 2024View details →

Properties of selected alkali-activated materials for sustainable development

<p>The presented research focuses on three selected variants of alkali-activated materials, where the goal is to compare key properties from the point of view of material engineering and structural design. Tests of the mechanical properties of the examined materials are carried out and their durability is compared, namely frost resistance, resistance to chemical and de-icing substances and resistance to elevated temperature.</p>

Data for Marshall et al, "Microbial metabolism disrupts cytokine activity to impact host immune response"

<p>Raw data for publication "Microbial metabolism disrupts cytokine activity to impact host immune response", Marshall EKP et al. The archive is organized into folders containing raw data pertaining to each figure.</p>