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9,113 results for “Sampling”
DCSsim (simulated) and DCSsub (sub-sampled) ChIP-seq data from different chromosomes.
<p>These data are the results from three independent runs of DCSsim and DCSsub for TF, sharp and broad mark signals in 50:50 regulation scenarios for mm10 chr1, chr8, chr11, chr19 and chrX.</p> <p>Simulated data from DCSsim: simulated_ChIP-seq_data.zip</p> <p>set1: TF 50:50 chr11<br> set4: TF 50:50 chr8<br> set7: TF 50:50 chrX<br> set10: TF 50:50 chr1<br> set22: TF 50:50 chr19</p> <p>set2: Sharp mark 50:50 chr11<br> set5: Sharp mark 50:50 chr8<br> set8: Sharp mark 50:50 chrX<br> set11: Sharp mark 50:50 chr1<br> set23: Sharp mark 50:50 chr19</p> <p>set3: Broad mark 50:50 chr11<br> set6: Broad mark 50:50 chr8<br> set9: Broad mark 50:50 chrX<br> set12: Broad mark 50:50 chr1<br> set24: Broad mark 50:50 chr19</p> <p><br> Sub-sampled data from DCSsub: sub-sampled_ChIP-seq_data.zip</p> <p>Set1: C/EBPa-ChIP-seq 50:50 chr11<br> Set2: C/EBPa-ChIP-seq 50:50 chr8<br> Set3: C/EBPa-ChIP-seq 50:50 chrX<br> Set4: C/EBPa-ChIP-seq 50:50 chr1</p> <p>Set5: H3K27ac-ChIP-seq 50:50 chr11<br> Set6: H3K27ac-ChIP-seq 50:50 chr8<br> Set7: H3K27ac-ChIP-seq 50:50 chrX<br> Set8: H3K27ac-ChIP-seq 50:50 chr1</p> <p>Set9: H3K36me3-ChIP-seq 50:50 chr11<br> Set10: H3K36me3-ChIP-seq 50:50 chr8<br> Set11: H3K36me3-ChIP-seq 50:50 chrX<br> Set12: H3K36me3-ChIP-seq 50:50 chr1</p> <p><br> C/EBPa-ChIP-seq 50:50 chr19 can be found in sub-sampled_ChIP-seq_data.zip of the FRIP data set (DOI: 10.5281/zenodo.6042902 set8)<br> H3K27ac-ChIP-seq 50:50 chr19 can be found in sub-sampled_ChIP-seq_data.zip of the FRIP data set (DOI: 10.5281/zenodo.6042902 set9)<br> H3K36me3-ChIP-seq 50:50 chr19 can be found in sub-sampled_ChIP-seq_data.zip of the FRIP data set (DOI: 10.5281/zenodo.6042902 set10)</p>
Mapping of samples – Deliverables in WP3: Novel pyrolysis oil from non-food/feed biomass
<p>In the H2020-project BioMates (www.biomates.eu, see chapter 4 “Funding and disclaimer”), RISE produced samples from ablative fast pyrolysis of herbaceous biomass in a TRL 5-plant. A dedicated document provides identifiers for relevant liquid samples and their blends [1]. The document at hand maps it to the substances reported to be used in the public deliverables and public deliverable summaries connected to Work Package 3 “Technology scale up and validation” of the BioMates-project, as far as mapping is not provided in the documents themselves.</p>
Dataset: A systematic multi-technique comparison of luminescence characteristics of two reference quartz samples
<p>Original dataset corresponding to the manuscript Schmidt et al. submitted to the Journal of Luminescence. The dataset is structured as follows: </p> <ul> <li>01_original_data <ul> <li>This folder contains the original measurement data for each experiment (e.g., LM-OSL, TL), organised following the manuscript figures, e.g., Fig_4. These subfolders contain the original measurement data and the measurement sequence. For Risø readers, the output format is *.binx and *.xsyg for results from the Freiberg Instruments lexsyg readers (e.g., TR-OSL).</li> </ul> </li> <li>02_processed_data <ul> <li>Comma-separated value (*.csv) to reproduce each figure in the manuscript. </li> </ul> </li> </ul> <p> </p>
Sample ECCOH OH Parameterization
<p>A sample parameterization of OH for July created to be used with the ECCOH module of the GEOS Earth System Model. The methodology to generate the parameterization is described in detail in the GMD article "A Machine Learning Methodology for the Generation of a Parameterization of the Hydroxyl Radical". The parameterization is included as an example and should not be used for research purposes without consulting the publication and/or the authors. We have also included the dataset used to train the parameterization (OHParameterization_TrainingSet_1980_2019_M07.dat) as well as the training targets (OHParameterization_Targets_1980_2019_M07.dat). The training data are from the NASA MERRA2 GMI simulation (https://acd-ext.gsfc.nasa.gov/Projects/GEOSCCM/MERRA2GMI/). The scripts used to generate the training dataset and the parameterization can be found at https://zenodo.org/record/6046037. </p>
NYC telematics data with asynchronous sampling
<p>This telematics data are used in the paper "Alrassy, P., Jang, J., and Smyth, A. W. (2021). "OBD-data-assisted cost-based map-matching algorithm for low-sampled telematics data in urban environments." IEEE Transactions on Intelligent<br> Transportation Systems. doi:10.1109/TITS.2021.3109851</p> <p>The data were collected in New York City. Each trajectory represents 15 to 30 minutes of driving. An in-vehicle sensing hardware package is developed and comprises a Raspberry PI 3 Model B+ microcomputer, a microSD 32GB SD card, an OBDCheck BLE OBD-II scanner, and a GPS module. This sensor configuration aims to collect timestamps, GPS positioning, and instantaneous speed data. Each sensor module has a dedicated data collection algorithm to collect data whenever new data updates are available on the sensor node. The structure of the data follows:</p> <p>Data Type, timestamp, values</p> <p>GPS, timestamp, latitude, longitude, altitude</p> <p>OBD, timestamp, RPM, speed</p>
D4.1. YouCount open data sample from the evaluation – current stand
<p>The H2020 YouCount project runs from February 2021 to January 2024. The overarching objectives are to generate new knowledge and innovations to increase the social inclusion of youth through co-creative youth citizen social science (Y-CSS) and to provide evidence of the actual outcomes of Y-CSS. Multiple case studies—consisting of 10 co-creative Y-CSS projects with young citizen scientists (YCS) aged between about 13-29 years old across nine countries in Europe—will provide knowledge about the positive drivers of social inclusion in general. The cases will further produce knowledge as well as innovations in relation to social participation, social belonging, and citizenship.</p> <p>The YouCount evaluation design for process and outcome evaluation of Y-CSS is a multi-method approach that spans across the whole duration of the project and is carried out by the WP4 of UNIVIE. It therefore is to be classified as current work in progress, as some methods only just have been implemented and will be analyzed in the future, to estimated cross-case comparisons. The deliverable aims at making the research design, as well as the current stand of the evaluative studies, transparent and publicly available. This happens in the spirit of open science, with the goal of doing “Science for and with Society”. Hereby outlined is the theoretical design, the way of carrying it out, and the current stand of each study implementation in the overall project.</p> <p>Moreover, the D4.1 includes open data regarding the outcome methodology (pre-survey questionnaire) and a sav.file with a sample of open data collected from the current pre-survey data. See more details in the report. The attached sav.-file can provide knowledge about the used variables, to estimate occurring answering patterns very roughly, ad to familiarize with the implementation of such a pre-post-survey. However, it is to be noted that this data set is exemplary, anonymized and potentially also not complete yet and must be handled and used accordingly. Due to the relatively low number of participants (yet), this research is to be characterized as early stage research and only depicts a moment in time. This being said, the YouCount project is designed to gather a huge quantity of data that promises a variety of concrete research outputs, so future data samples will be richer for in-depth analyses. At this point, more quantitative as well as qualitative data is needed to estimate real impacts of Y-CSS in all its facettes.</p>
Data of FigS7, "The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples"
<p>Data of FigS7, “The Potential Tumor-Suppressor DHRS7 Inversely Correlates with EGFR Expression in Prostate Cancer Cells and Tumor Samples”</p> <p>The Dataset (original publication: doi: 10.3390/cancers14133074) contains the original figure as PNG-format (10.3390-cancers14133074_FigS7.PNG). The Corresponding raw data and subsequent data analysis obtained contains one file in txt-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_23_1_M .txt) and one file as csv-format (31003A-179400_10.3390-cancers14133074_SSDHRS7_12_1.csv).</p>
eDNAbyss samples provenance and environmental context - version 1
<p>This is a tabular version of the eDNAbyss sample provenance & environmental context metadata submitted to BioSamples (<a href="https://www.ebi.ac.uk/biosamples/samples?text=eDNAbyss">https://www.ebi.ac.uk/biosamples/samples?text=eDNAbyss</a>).</p>
Data Providers Samples DB v2
<p>This dataset describes the data samples uploaded by the data providers to the REACH Data Catalogue for both OC1 and OC2. </p>
Data for conductance-based simulations of "Cortical oscillations support sampling-based computations in spiking neural networks"
<p>This repository contains the full data generated by the conductance-based simulations described in: <a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009753">Cortical oscillations support sampling-based computations in spiking neural networks</a>. The code is accessible via <a href="https://doi.org/10.5281/zenodo.5512526.">this repository</a>.</p>
Database with GRTS sampling design used for the C-Mon project.
<p> A SQLite database holding a realisation of a GRTS design using the principles of Reverse Randomized Quadrant-Recursive Raster method (Theobold et al 2007). The database covers a square 2D grid with 32768 (2^15) pixels in both dimensions. This allows aselect and spatially balanced sampling in <a href="https://www.openstreetmap.org/relation/53134">Flanders</a> (Belgium) at 10 x 10 m resolution. In the framework of the C-Mon project, selection of plots for sampling soil organic carbon (SOC) stocks over all landuses is performed based on this realisation. It is envisaged that the plots will be monitored over decades to quantify SOC stock changes over time, along with landuse changes. . </p> <p>The R script used to generate the database and to sample from the database is provided. The algorithm itself is available on <a href="https://github.com/inbo/grtsdb/releases/tag/v0.1">GitHub</a> (10.5281/zenodo.2784016).</p> <p>The C-Mon project, entitled (in Dutch): 'Actualisatie van de onderbouwing van een methodiek voor de systematische monitoring van koolstofvoorraden in de bodem' was financed by the Department Vlaams Planbureau voor Omgeving from the Flemish Government. Project-ID: OMG/VPO/BODEM/TWOL/2017/1 </p>
Linkage-independent SNPs in the Drosophila melanogaster Sussex LHM sample
<p>Unix code for running Plink program for generating a list of SNPs (single-nucleotide polymorphisms) which are independent of linkage diseqiulibrium. Used for later statistical analyses incorporating the number of independent tests made across the genome.</p>
Separate-sex GWAS for reproductive fitness in Drosophila melanogaster (Sussex LHM sample)
<p>Code, data, logs, and graphs for GWAS on seperate-sex reproductive fitness in Drosophila melanogaster, Sussex LHM population sample.</p> <p>The shell script, code_drive_basic_gwas.sh, downloads input data files from the internet, drives Plink to select LD-independent SNPs, and then perform a genome-wide association test against female and male fitness, separately. Plink is also used to assign functions and gene names to SNPs. Bash/Unix code is used for formatting/compatibility adjustments, and also to add NCBI-dbSNP IDs to results. The shell script starts an R script that generates basic diagnostic graphs. This updated version differs from the first in that three large unconfirmed snRNA genes have been omitted to improve assignment of SNPs to genes.</p> <p>See https://f1000research.com/articles/5-2644/v3 and http://www.sussex.ac.uk/lifesci/morrowlab/</p>
False discovery rate calculations for genome-wide association study of reproductive fitness in Drosophila melanogaster (Sussex LHM sample)
<p>R code and results of applying false discovery (FDR) rate calculations to establish statistical signficance in a genome-wide association study of reproductive fitness in Drosophila melanogaster. Phenotype values were generated on hemiclone female and male lines from an outbred, laboratory adapted population. Thus, GWAS were previously performed seperately on the phenotype values for each sex, and also using a bivariate GWAS implemented in the R package multiPhen.</p> <p>FDR calculations were performed using the R package 'fdrtool' on all SNPs, and on LD-independent SNPs, the latter of which was used to determine p-value thresholds for genome-wide significance when all SNPs were considered.</p> <p>This version differs from the original in that: i) Some gene positions/names have been reassigned for accuaracy in the input data. ii) A file containing the p-value thresholds corresponding to an FDR of 0.1 has been added. The 95% credible intervals for each SNP association have been added to the results data files.</p>
Octomap samples.
<p>circle, double_circle and s are octomap samples of octomaps of simulated smaller scenarios. Circle is a room with a door. Double circle is a circular corridor with one interior opening. S is a s shaped corridor with openings on both sides.</p> <p>Off shore oil are in the same large simulated scenario. Where 4 pillars simulate the pillars of an oil rig. oilrig is the sample after exploring only two pillars. 4 obstacles is after exploring 3 pillars (but has information about the forth.</p> <p>experimental dataset was generated from a flight in a 15 x 15 x 5 interior testbed with obstacles simulating a factory.</p> <p>Sensor at 1 meter.</p>
Peak Flow Event Durations in the Mississippi River Basin and Implications for Temporal Sampling of Rivers
<p><strong>Corresponding peer-reviewed publication</strong></p> <p>This repository corresponds to all the input and output files that were used in the study reported in:</p> <ul> <li>Cerbelaud, A., David, C. H., Biancamaria, S., Wade, J., Tom, M., Prata de Moraes Frasson, R., & Blumstein, D. (2024). Peak flow event durations in the Mississippi River basin and implications for temporal sampling of rivers. Geophysical Research Letters, 51, e2024GL109220. <a href="https://doi.org/10.1029/2024GL109220" target="_blank" rel="noopener">https://doi.org/10.1029/2024GL109220</a>.</li> </ul> <p>When making use of any of the output files of this dataset, please cite both the aforementioned article and the dataset herein. </p> <p><strong>Main goals of the publication</strong></p> <p>The corresponding work aims to quantify peak flow event durations at an hourly time scale and their impact on high-frequency river sampling requirements using sampling ratios. The analysis is performed over the Mississippi basin using hourly USGS gages over 2010-2022.</p> <p>The findings derived from these output files have direct implications for future satellite missions concerned with capturing high-frequency dynamics in rivers, including flood events.</p>
Raw luminescence data for samples from Abri 122/1200 (Vârghiș Gorges, Romania)
<p>The files contain the raw luminescence data used to calculate the equivalent doses and ages cited in the study by Schmidt et al.: Evidence for the oldest Middle Palaeolithic cave occupation in the Romanian Carpathians.</p> <p>The .seq files contain the measurement parameters, while the .binx files contain the results (.binx files can be read by the Analyst software thta can be downloaded for free here: https://users.aber.ac.uk/ggd/).</p> <p>DRT: Dose recovery test</p> <p>PHP: Preheat plateau test</p> <p> </p> <p>The .csv files contain all parameters used to calculate the final ages, which were derived by using the software DRAC (Durcan et al., 2015). The two scenarios considering the shielding of the cave overburden for calculation of the cosmic dose rate refer to the two different .csv files, according to their name.</p> <p> </p>
Dataset from "A user-friendly method to get automated pollen analysis from environmental samples". New Phytologist.
<p>Dataset used in publication "A user-friendly method to get automated pollen analysis from environmental samples". New Phytologist.</p> <p><br>This repository contains images from annual pollen trap samples mounted on slides and scanned under light microscopy; image annotation metadata; and the weights of the trained models from the YOLOv5 algorithm, saved after the last training epoch.</p> <p>More details can be found in the README file.</p>
HipFT Sample Input Dataset for Convective Flows and Data Assimilation
<p>This file package is a sample data set for running <a href="https://www.github.com/predsci/hipft">HipFT</a> with convective flows and data assimilation. </p> <p>The convective flows were generated with the <a href="https://www.github.com/predsci/conflow">ConFlow</a> code (soon to be released), while the data assimilation maps were processed from HMI M720s LOS data using the <a href="https://www.github.com/predsci/MagMAP">MagMAP</a> package (also soon to be released).</p> <p>See the enclosed README file on how to run an example included in the HipFT package that uses the two data sets.</p>
Factual Report on XRF Analysis Conducted on Bulk Sedimentary Rock Samples from the Mesohellenic Trough
<p><strong><span>Factual Report on XRF Analysis Conducted on Bulk Sedimentary Rock Samples from the Mesohellenic Trough – Project: PilotStratergy</span></strong></p> <p><strong><span> </span></strong></p> <p><span>Analysis date: 30.04.2024 </span></p> <p><span>Report date: 02.05.2024, Revision date: -</span></p> <p><span>Written by: Christos L. Stergiou, Geologist, PhD</span></p> <p><span>Reviewed by: Pavlos Tyrologou, Geologist, PhD</span></p> <p><span>Advice also: Previous factual report files “Report_SEM_Round1_Bulk samples.docx” and “Report_XRD_PilotStrategy03.04.2024.docx” for additional information on the mineralogy of the samples included in this report. </span></p> <p><strong><span> </span></strong></p> <p><strong><span>1. Materials and Methods</span></strong></p> <p><span>Three (3) sedimentary rock samples originating from the Tsotyli (sample Tsot-1; marly SANDSTONE), Eptachori (sample Ept-2; fine GREYWACKE) and Pentalofos (sample Pent-3; greywacke) Formations of the Mesohellenic Trough were powdered and analyzed by X-ray fluorescence (XRF) to determine their mineralogical composition. The samples were field collected by hummer and obtained as rock chips. Pulps produced from the rock chip samples were formed into pressed pellets by mixing 2.4 g of the binder CEREOX® with 9.6 g of rock pulp (i.e. sample-to-wax binder ratio of 4:1). The mixed material was homogenized in a mechanical mixer working at 24 rpm for 15 minutes and then pressed at 5 kbr (Fig. 2). The XRF analysis was performed using Bruker S4-PIONEER with a wavelength-dispersive X-ray fluorescence (WDXRF) analytical system at the Department of Mineralogy-Petrology-Economic Geology, School of Geology, Aristotle University of Thessaloniki. The spectrometer uses an Rh lamp and a system of 5 crystals: LIF200, LIF220, LIF420, XS-55, and PET. It also has two detectors: a gas proportional counter and a scintillation counter. The X-ray beam was used at its maximum energy of 50-60 kV. The element lines that were measured were the Ka and La lines, depending on the element. The method includes corrections for overlaps and matrix effects. Analytical results are presented in Table 1, while major conclusions after XRF analysis are presented below by taking into consideration conclusions previously made after XRD and SEM-EDS analysis. Previous published investigations on these samples include geomechanical and petrophysical methods for the evaluation of the parent sedimentary formations to capture and store CO<sub>2</sub> (Tyrologou et al. 2023).</span></p> <p><strong><span> </span></strong></p> <p> </p> <p><strong><span>Table 1.</span></strong><span> Bulk geochemical analyses of major and minor elements for the analyzed samples Tsot-1, Ept-2 and Pent-3 from the Mesohellenic Trough.</span></p> <p><span> </span></p> <div> <table> <tbody> <tr> <td> <p><strong><span>Element</span></strong></p> </td> <td> <p><strong><span>Tsot-1</span></strong></p> </td> <td> <p><strong><span>Ept-2</span></strong></p> </td> <td> <p><strong><span>Pent-3</span></strong></p> </td> </tr> <tr> <td> <p><em><span>wt.%</span></em></p> </td> <td> <p><span> </span></p> </td> <td> <p><span> </span></p> </td> <td> <p><span> </span></p> </td> </tr> <tr> <td> <p><span>SiO<sub>2</sub></span></p> </td> <td> <p><span>34.85</span></p> </td> <td> <p><span>36.25</span></p> </td> <td> <p><span>15.49</span></p> </td> </tr> <tr> <td> <p><span>Al<sub>2</sub>O<sub>3</sub></span></p> </td> <td> <p><span>7.18</span></p> </td> <td> <p><span>6.61</span></p> </td> <td> <p><span>2.9</span></p> </td> </tr> <tr> <td> <p><span>Fe<sub>2</sub>O<sub>3</sub></span></p> </td> <td> <p><span>2.66</span></p> </td> <td> <p><span>3.32</span></p> </td> <td> <p><span>1.22</span></p> </td> </tr> <tr> <td> <p><span>CaO</span></p> </td> <td> <p><span>30.27</span></p> </td> <td> <p><span>25.61</span></p> </td> <td> <p><span>42.42</span></p> </td> </tr> <tr> <td> <p><span>MgO</span></p> </td> <td> <p><span>4.23</span></p> </td> <td> <p><span>7.23</span></p> </td> <td> <p><span>5.98</span></p> </td> </tr> <tr> <td> <p><span>Na<sub>2</sub>O</span></p> </td> <td> <p><span>1.04</span></p> </td> <td> <p><span>0.74</span></p> </td> <td> <p><span>0.39</span></p> </td> </tr> <tr> <td> <p><span>K<sub>2</sub>O</span></p> </td> <td> <p><span>2.22</span></p> </td> <td> <p><span>1.39</span></p> </td> <td> <p><span>0.94</span></p> </td> </tr> <tr> <td> <p><span>MnO</span></p> </td> <td> <p><span>0.11</span></p> </td> <td> <p><span>0.11</span></p> </td> <td> <p><span>0.03</span></p> </td> </tr> <tr> <td> <p><span>TiO<sub>2</sub></span></p> </td> <td> <p><span>0.32</span></p> </td> <td> <p><span>0.39</span></p> </td> <td> <p><span>0.13</span></p> </td> </tr> <tr> <td> <p><span>P<sub>2</sub>O<sub>5</sub></span></p> </td> <td> <p><span>0.08</span></p> </td> <td> <p><span>0.1</span></p> </td> <td> <p><span>0.06</span></p> </td> </tr> <tr> <td> <p><span>LOI</span></p> </td> <td> <p><span>16.79</span></p> </td> <td> <p><span>17.89</span></p> </td> <td> <p><span>30.3</span></p> </td> </tr> <tr> <td> <p><span>Total</span></p> </td> <td> <p><span>99.75</span></p> </td> <td> <p><span>99.64</span></p> </td> <td> <p><span>99.86</span></p> </td> </tr> <tr> <td> <p><em><span>ppm</span></em></p> </td> <td> <p><span> </span></p> </td> <td> <p><span> </span></p> </td> <td> <p><span> </span></p> </td> </tr> <tr> <td> <p><span>Ba</span></p> </td> <td> <p><span>189</span></p> </td> <td> <p><span>149</span></p> </td> <td> <p><span>66</span></p> </td> </tr> <tr> <td> <p><span>Co</span></p> </td> <td> <p><span>7</span><span>.0</span></p> </td> <td> <p><span>13</span></p> </td> <td> <p><span>4</span><span>.0</span></p> </td> </tr> <tr> <td> <p><span>Cr</span></p> </td> <td> <p><span>749</span></p> </td> <td> <p><span>1</span><span>,</span><span>680</span></p> </td> <td> <p><span>512</span></p> </td> </tr> <tr> <td> <p><span>Cu</span></p> </td> <td> <p><span>14</span></p> </td> <td> <p><span>23</span></p> </td> <td> <p><span>7</span><span>.0</span></p> </td> </tr> <tr> <td> <p><span>Ni</span></p> </td> <td> <p><span>112</span></p> </td> <td> <p><span>221</span></p> </td> <td> <p><span>78</span></p> </td> </tr> <tr> <td> <p><span>Rb</span></p> </td> <td> <p><span>192</span></p> </td> <td> <p><span>95</span></p> </td> <td> <p><span>82</span></p> </td> </tr> <tr> <td> <p><span>Sc</span></p> </td> <td> <p><em><span>bdl</span></em></p> </td> <td> <p><em><span>bdl</span></em></p> </td> <td> <p><em><span>bdl</span></em></p> </td> </tr> <tr> <td> <p><span>Sr</span></p> </td> <td> <p><span>298</span></p> </td> <td> <p><span>342</span></p> </td> <td> <p><span>242</span></p> </td> </tr> <tr> <td> <p><span>V</span></p> </td> <td> <p><span>650</span></p> </td> <td> <p><span>990</span></p> </td> <td> <p><span>306</span></p> </td> </tr> <tr> <td> <p><span>Zn</span></p> </td> <td> <p><span>31</span></p> </td> <td> <p><span>38</span></p> </td> <td> <p><span>15</span></p> </td> </tr> <tr> <td> <p><span>Zr</span></p> </td> <td> <p><span>100</span></p> </td> <td> <p><span>113</span></p> </td> <td> <p><span>54</span></p> </td> </tr> </tbody> </table> </div> <p><span>*LOI = Loss of ignition, bdl = below detection limit.</span></p> <p><strong><span> </span></strong></p> <p><strong><span>5. Conclusions</span></strong></p> <p><span>The XRF analysis confirms suggestions and conclusions made on previously acquired SEM-EDS and XRD analytical results focusing on bulk samples obtained by hammering from marly SANDSTONE (Tsot-1) and greywacke (Ept-2, Pent-3) originating from the Tsotyli, Eptachori and Pentalofos Formations of the Mesohellenic Trough (Fig. 1).</span></p> <p><span>Bulk geochemical analysis reveals that calcium and silica are the most enriched elements (Table 1). Sample Tsot-1 (24.85 wt.% </span><span>SiO<sub>2</sub>)</span><span> is slightly siliceous in composition, sample Epth-2 (36.25 wt.% </span><span>SiO<sub>2</sub>)</span><span> is dominantly siliceous, while sample Pent-3 is dominantly calcareous in composition (42.42 wt.% CaO, Table 1). These results are complementary to the semi-quantitative estimates obtained by XRD analysis (cf. Report_XRD_PilotStrategy03.04.2024.docx). In sample Tsot-1, calcite content is 30 wt.%, while quartz (29 wt.%) and albite (19 wt.%) percentages sum to 50 wt.%, supporting the siliceous profile acquired by XRF. In sample Ept-2, quartz (37 wt.%) is the dominant mineral phase followed by calcite (29 wt.%), while in sample Pent-3, calcite (41 wt.%) is the more enriched mineral phase, supporting the obtained geochemical results where </span><span>SiO<sub>2</sub></span><span> is 36.25 wt.% in sample Ept-2 and </span><span>CaO is 45.42 wt.% for sample Pent-3. In addition, the geochemical results support the suggested level of maturity of the analyzed samples with Etp-2 showing the highest and Pent-3 the lowest maturity.</span></p> <p><span>Finally, sample Ept-2 shows the highest enrichment in minor elements, including 1,680 ppm of Cr and 990 ppm of V (Table 1). Relative enrichments in these trace elements, as well as in Co, Cu, Ni and Zn could be related to the highest incorporation of detrital material related to the ophiolitic basement rocks of the Mesohellenic Trough. Variations in trace elements may be associated with minor mineral phases not detected by the XRD analysis and the SEM-EDS examination of bulk samples. </span><span>The study of thin-polished sections under a plane polarized and an electron scanning microscope shall clarify the mineral composition of the samples and conclude the mineralogical and geochemical investigation.</span></p> <p><span> </span></p> <p><strong><span>6. References</span></strong></p> <p><span>Tyrologou, Pavlos, et al. (2023). Progress for carbon dioxide geological storage in West Macedonia: A field and laboratory-based survey." Open Research Europe 3. https://doi.org/10.12688/openreseurope.15847.2</span></p> <p><span> </span></p>
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International Brain Laboratory public data
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OpenNeuro
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