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Serneels, S.; Faber, K.; Verdonck, T.; van Espen, P.J. |
![goto web page (via DOI) doi](http://nano.uantwerpen.be/nanorefs/img/doi.gif)
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Title |
Case specific prediction intervals for tri-PLS1 : the full local linearisation |
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A1 Journal article |
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Year |
2011 |
Publication |
Chemometrics and intelligent laboratory systems |
Abbreviated Journal |
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108 |
Issue |
2 |
Pages |
93-99 |
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Keywords |
A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation) |
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Abstract |
A new method to estimate case specific prediction uncertainty for univariate trilinear partial least squares (tri-PLS1) regression is introduced. This method is, from a theoretical point of view, the most exact finite sample approximation to true prediction uncertainty that has been reported up till now. Using the new method, different error sources can be propagated, which is an advantage that cannot be offered by data driven approaches such as the bootstrap. In a concise example, it is illustrated how the method can be applied. In the Appendix, efficient algorithms are presented to compute the estimates required. |
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Wos |
000295310000002 |
Publication Date |
2011-05-12 |
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ISSN |
0169-7439; 1873-3239 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Open Access |
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no |
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Call Number |
UA @ admin @ c:irua:92788 |
Serial |
7580 |
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Permanent link to this record |
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Author |
Calogiuri, T.; Hagens, M.; Van Groenigen, J.W.; Corbett, T.; Hartmann, J.; Hendriksen, R.; Janssens, I.; Janssens, I.A.; Ledesma Dominguez, G.; Loescher, G.; Mortier, S.; Neubeck, A.; Niron, H.; Poetra, R.P.; Rieder, L.; Struyf, E.; Van Tendeloo, M.; De Schepper, T.; Verdonck, T.; Vlaeminck, S.E.; Vicca, S.; Vidal, A. |
![goto web page (via DOI) doi](http://nano.uantwerpen.be/nanorefs/img/doi.gif)
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Title |
Design and construction of an experimental setup to enhance mineral weathering through the activity of soil organisms |
Type |
A1 Journal article |
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Year |
2023 |
Publication |
Journal of visualized experiments |
Abbreviated Journal |
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Issue |
201 |
Pages |
e65563-30 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Internet Data Lab (IDLab); Applied mathematics; Sustainable Energy, Air and Water Technology (DuEL); Plant and Ecosystems (PLECO) – Ecology in a time of change |
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Abstract |
Enhanced weathering (EW) is an emerging carbon dioxide (CO2) removal technology that can contribute to climate change mitigation. This technology relies on accelerating the natural process of mineral weathering in soils by manipulating the abiotic variables that govern this process, in particular mineral grain size and exposure to acids dissolved in water. EW mainly aims at reducing atmospheric CO2 concentrations by enhancing inorganic carbon sequestration. Until now, knowledge of EW has been mainly gained through experiments that focused on the abiotic variables known for stimulating mineral weathering, thereby neglecting the potential influence of biotic components. While bacteria, fungi, and earthworms are known to increase mineral weathering rates, the use of soil organisms in the context of EW remains underexplored. This protocol describes the design and construction of an experimental setup developed to enhance mineral weathering rates through soil organisms while concurrently controlling abiotic conditions. The setup is designed to maximize weathering rates while maintaining soil organisms' activity. It consists of a large number of columns filled with rock powder and organic material, located in a climate chamber and with water applied via a downflow irrigation system. Columns are placed above a fridge containing jerrycans to collect the leachate. Representative results demonstrate that this setup is suitable to ensure the activity of soil organisms and quantify their effect on inorganic carbon sequestration. Challenges remain in minimizing leachate losses, ensuring homogeneous ventilation through the climate chamber, and avoiding flooding of the columns. With this setup, an innovative and promising approach is proposed to enhance mineral weathering rates through the activity of soil biota and disentangle the effect of biotic and abiotic factors as drivers of EW. |
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Wos |
001127854400015 |
Publication Date |
2023-11-12 |
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1940-087x |
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Additional Links |
UA library record; WoS full record |
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Impact Factor ![sorted by Impact Factor field, ascending order (up)](img/sort_asc.gif) |
1.2 |
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Open Access |
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Most recent IF: 1.2; 2023 IF: 1.232 |
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Call Number |
UA @ admin @ c:irua:200770 |
Serial |
9019 |
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Permanent link to this record |