<?xml version="1.0" encoding="UTF-8"?>
<feed xmlns="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
<title>eBiltegia</title>
<link href="https://ebiltegia.mondragon.edu:443" rel="alternate"/>
<subtitle>The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.</subtitle>
<id xmlns="http://apache.org/cocoon/i18n/2.1">https://ebiltegia.mondragon.edu:443</id>
<updated>2026-03-15T08:03:39Z</updated>
<dc:date>2026-03-15T08:03:39Z</dc:date>
<entry>
<title>CFD investigation of solid content influence on thermal sterilization of canned products</title>
<link href="https://hdl.handle.net/20.500.11984/14071" rel="alternate"/>
<author>
<name>Alonso de Mezquia, David</name>
</author>
<author>
<name>Lapeira, Estela</name>
</author>
<author>
<name>Bou-Ali, M. Mounir</name>
</author>
<id>https://hdl.handle.net/20.500.11984/14071</id>
<updated>2026-03-14T07:15:41Z</updated>
<published>2025-01-01T00:00:00Z</published>
<summary type="text">CFD investigation of solid content influence on thermal sterilization of canned products
Alonso de Mezquia, David; Lapeira, Estela; Bou-Ali, M. Mounir
The objective of this study is to analyze the impact of solid particle size on the thermal sterilization process of canned food using Computational Fluid Dynamics (CFD). The study investigates how different particle sizes influence heat transfer efficiency, heating rate, and overall process lethality. A CFD-based model, validated against experimental data, is employed to assess temperature distribution and determine the slowest heating zone (SHZ) for various particle configurations.
</summary>
<dc:date>2025-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Deep Learning-based age prediction models from retinal Optical Coherence Tomography images</title>
<link href="https://hdl.handle.net/20.500.11984/14070" rel="alternate"/>
<author>
<name>Zuazo Atutxa, Garazi</name>
</author>
<author>
<name>Ayala, Unai</name>
</author>
<author>
<name>Gabilondo Cuellar, Iñigo</name>
</author>
<author>
<name>Barrenechea, Maitane</name>
</author>
<id>https://hdl.handle.net/20.500.11984/14070</id>
<updated>2026-03-14T07:15:41Z</updated>
<published>2025-01-01T00:00:00Z</published>
<summary type="text">Deep Learning-based age prediction models from retinal Optical Coherence Tomography images
Zuazo Atutxa, Garazi; Ayala, Unai; Gabilondo Cuellar, Iñigo; Barrenechea, Maitane
This study evaluates the potential of Optical Coherence Tomog&#13;
raphy (OCT) as a non-invasive tool for retinal age prediction in&#13;
healthy individuals. A dataset comprising 1,180 eyes from 517 con&#13;
trol subjects was used to compare deep learning models trained on&#13;
different OCT scan types: peripapillary B-scans, individual macula&#13;
raster B-Scans, and full macular volumes. Images underwent stan&#13;
dardized preprocessing, and models based on 2D and 3D ResNet&#13;
architectures were trained and optimized using Transfer Learning.&#13;
Results show that volumetric macular scans applied in a ResNet&#13;
3D model achieved the lowest Mean Absolute Error (3.07 years),&#13;
outperforming both previous literature and all tested 2D configura&#13;
tions. Overall, findings highlight that integrating depth and spatial&#13;
features in OCT data significantly enhances retinal age estimation.
</summary>
<dc:date>2025-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Exploring the relationship between the gender composition of senior company bodies and surplus distribution in worker cooperatives in the MONDRAGON Corporation</title>
<link href="https://hdl.handle.net/20.500.11984/14069" rel="alternate"/>
<author>
<name>Ibarzabal-Zulaika, Ainhoa</name>
</author>
<author>
<name>Arenaza-Bengoa, Iñaki</name>
</author>
<author>
<name>Herce-Lezeta, Beñat</name>
</author>
<author>
<name>Freundlich, Frederick</name>
</author>
<id>https://hdl.handle.net/20.500.11984/14069</id>
<updated>2026-03-13T07:15:48Z</updated>
<published>2025-12-01T00:00:00Z</published>
<summary type="text">Exploring the relationship between the gender composition of senior company bodies and surplus distribution in worker cooperatives in the MONDRAGON Corporation
Ibarzabal-Zulaika, Ainhoa; Arenaza-Bengoa, Iñaki; Herce-Lezeta, Beñat; Freundlich, Frederick
This study examines the influence of gender composition of the governing council (GC) and senior management council (SMC) of worker cooperatives on the distribution of cooperative surplus. The analysis relies on a panel dataset of 383 observations from 82 worker cooperatives, member firms of the MONDRAGON Corporation, over the period 2010–2022. Using the System generalized method of moments panel data methodology, the results indicate that gender composition does have an impact. Data on GCs’ gender composition on surplus distribution suggest that a higher proportion of women on these councils is associated with lower surplus allocations, in line with the substitution perspective of agency theory and several studies on women's behaviour in decision-making bodies. Conversely, in the case of the SMCs, a positive relationship is observed between the proportion of women and surplus distribution. Although agency conflicts should be minimal in the cooperative context, the different results observed between the two governance bodies suggest that certain agency effects may be present. This suggests that the configuration and functioning of decision-making bodies can play a key role in how surpluses are managed and distributed. These findings contribute to the literature by advancing our understanding of gender effects on senior-level financial decision-making processes in worker cooperatives.
</summary>
<dc:date>2025-12-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Organisational learning structures favour knowledge transfer in succession planning</title>
<link href="https://hdl.handle.net/20.500.11984/14068" rel="alternate"/>
<author>
<name>Sánchez Urien, Nerea</name>
</author>
<author>
<name>Castaño-Benito, Uxue</name>
</author>
<author>
<name>Alonso-Andreano, José Luis</name>
</author>
<author>
<name>Ullibarriarana Garate, Ainhoa</name>
</author>
<id>https://hdl.handle.net/20.500.11984/14068</id>
<updated>2026-03-13T07:15:47Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">Organisational learning structures favour knowledge transfer in succession planning
Sánchez Urien, Nerea; Castaño-Benito, Uxue; Alonso-Andreano, José Luis; Ullibarriarana Garate, Ainhoa
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
</feed>
