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datasets available to search
ShareScore release 0.9.0
Dataset results
27 results for “TGA”
Fibrosis, Valvular and Ventricular Function in Patients With TGA
ClinicalTrials.gov study NCT02588989. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Transient Global Amnesia (TGA). Exploratory Study of the Default Mode Network During the Acute Phase
ClinicalTrials.gov study NCT02010853. IPD Sharing: NO. Countries: 1. Publications: 0.
Thrombomodulin-modified Thrombin Generation Assay (TGA-TM) in Patients With Critical Infections
ClinicalTrials.gov study NCT04356144. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Integration of shoot-derived polypeptide signals by root TGA transcription factors is essential for survival under fluctuating nitrogen environments [RNA-seq]
GEO Series GSE240736. Arabidopsis thaliana. 5 samples. Type: Expression profiling by high throughput sequencing.
Identification of TGA-regulated genes in response to phytoprostane A1 and OPDA
GEO Series GSE10732. Arabidopsis thaliana. 18 samples. Type: Expression profiling by array.
PP recyclates characterization after different samplings and recycling strategies-TGA
<p>PP-recyclates characterization after different sampling and recycling strategies – TGA data</p> <p>Authors: A. Martínez García, A. Ibáñez García, M.A. León Cabezas<br>Innovative Materials and Manufacturing Area, AIJU, Avda. de la Industria, 23 03440 Ibi (Alicante), Spain <br>Contact Information<br>email: sunymartinez@aiju.es<br>tel: +34 965554475</p> <p>This dataset contains raw TGA data of PP-recyclates from different recycling strategies following different sampling strategies.</p> <p>The purpose of this analysis is to evaluate the efficiency of the different recycling strategies and the quality of the resulting recyclates in combination with other analysis techniques.</p> <p>Recycling strategies followed: </p> <p>1) Purification of PP-rich post-consumer waste using supercritical CO2 (scCO2). scCO2 does not alter particle size or shape. <br>The waste material was subjected to scCO2 treatment in two ways. <br>The first method involved directly treating the flake material, which was subsequently ground. These samples are labelled CO-PP03RE-SC01GR. <br>The second approach aimed to investigate whether cleaning efficiency depends on particle size. <br>The flakes were ground first, and scCO2 was then applied to the particles, resulting in a sample identified as CO-PP03RE-GRSC01. <br>Homogenous powder was obtained in both cases and five samples were analysed following the DSC <br>For the sample preparation, the flakes of the waste were ground using a ring sieve mill (ZM 300, Retsch, Haan, Germany). </p> <p>Data from this approach are given in: PP recyclates after sc-CO2 recycling-TGA.xlsx</p> <p> <br>2) Purification of PP-rich post-consumer waste using solvent-based CreaSolv® process, developed by Fraunhofer IVV. <br>The solvent-based recycling process results in more homogeneous recyclates by dissolving the entire sample, and selectively precipitating the desired purified polymer, with the potential of removal of unwanted components. <br>The waste material was subjected to solvent-based recycling treatment in two ways. <br>The first method includes additional purification with a solid-liquid separation step, referred to as CO-PP03RE-CS+SL. </p> <p>The second method is without this additional purification, labelled as CO-PP03RE-CS-SL. <br>Homogeneous powder was obtained through solvent-based recycling process and five samples were analysed directly following the parallel plate rheology protocol. </p> <p>Data from this approach are given in: PP recyclates after solvent-based recycling-TGA.xlsx </p> <p>3) Purification of PP-rich post-consumer waste after upcycling and compounded by mechanical reprocessing.<br>The waste material was compounded after the reformulation with additives to enhance specific properties.<br>The material was subjected to compounding by means of remelting-restabilization, labelled as CO-PP03RE-CO.<br>Homogenous pellets were obtained through compounding recycling process.</p> <p>Data from this approach are given in: PP recyclates after upcycling-TGA.xlsx</p> <p>Reference samples: <br>PP-rich waste flakes were ground using a ring sieve mill to a particles size below 750 µm. Five samples were analyzed. </p> <p>The nomenclature followed is presented in the Table below:</p> <p>Recyclate Nomenclature Description<br>CO-PP03RE-GR PP Recyclate after cryogenic grinding (reference material)<br>CO-PP03RE-CO (Brug) PP Recyclate after compounding with Bruggolen <br>CO-PP03RE-GRSC01 PP Recyclate after cryogenic grinding and scCO2<br>CO-PP03RE-SC01GR PP Recyclate after scCO2 and cryogenic grinding<br>CO-PP03RE-CR-SL PP Recyclate after Creasolv without solid-liquid separation<br>CO-PP03RE-CR+SL PP Recyclate after Creasolv with solid-liquid separation</p>
ABS-rich model waste characterisation for different sampling strategies – TGA data
<p>The purpose of this analysis is the development of an efficient sampling protocol for plastic waste streams. </p> <p>A model waste from different polymers was formulated, rich in ABS and containing PS, PP and PE in smaller proportions. Additionally, one bromine containing flame retardant is added to a final concentration of either 500ppm or 50ppm. Different sampling approaches were followed including extrusion and/or cryogenic grinding as a homogenization step. Each approach was assessed via various analytical techniques as to homogenization efficiency. </p> <p>This dataset contains raw TGA data of the model waste from the different sampling approaches. The content is:</p> <p>·One Excel file containing TGA data of the model waste, wherein the approach was based on extrusion and measurement protocol</p> <p>·One Excel file containing TGA data of the model waste, wherein the approach was based on cryogenic grinding and measurement protocol</p> <p>·One Word file containing further information about the methodology and nomenclature </p> <p>This dataset was generated in the framework of PRecycling Horizon Europe project (101058670)</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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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.