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Slide 1 of 5 Publicación Acceso Abierto
Magnitude-dependent quantum advantage in Forbush decrease detection: A quantum kernel SVM benchmark
(Astronomy and Computing, 2026-07-04) Sierra Porta, David; Grupo de Investigación Gravitación y Matemática Aplicada; Semillero de Investigación en Astronomía y Ciencia de Datos
Forbush decreases (FDs) — transient reductions in galactic cosmic ray intensity driven by interplanetary coronal mass ejections — are key observables in space weather monitoring, yet their automated detection from multivariate solar wind and neutron monitor time series remains a challenging classification problem. Here we report a systematic benchmark of quantum kernel support vector machines (QKSVM) for FD detection, in which the FD magnitude threshold emerges as the governing factor separating two distinct classification regimes. Using 2971 confirmed events from the Forbush Effects and Interplanetary Disturbances (FEID) catalogue, combined with hourly OMNI solar wind parameters — including interplanetary magnetic field (IMF) components, solar wind speed, proton density, proton temperature, and the Kp and Dst geomagnetic indices — and galactic cosmic ray count rates from the Jungfraujoch neutron monitor station (JUNG, NMDB), we construct a balanced FD versus quiet-time classification dataset and extract 121 statistical features across eleven physical channels. A ZZFeatureMap quantum kernel with 4–8 qubits is benchmarked against a classical radial basis function (RBF) SVM across 180 experimental configurations spanning FD magnitude thresholds of 0%–7%, circuit depths of 1–3 repetitions, and quantum training sizes of 50–250 samples. We find that below a magnitude threshold of 4%, the classical kernel consistently outperforms the quantum alternative (mean at min_magn %). Above this threshold, the relationship inverts: at min_magn % the quantum kernel achieves positive mean in 72% of configurations, rising to 100% of configurations at min_magn % (mean , peak with 4–8 qubits), indicating that the entanglement structure of the ZZFeatureMap captures non-linear correlations between IMF dynamics and cosmic ray modulation that the RBF kernel cannot represent. The magnitude threshold of 4% thus constitutes a physically interpretable boundary between a noise-dominated regime where classical methods suffice and a signal-rich regime where quantum kernels provide measurable and statistically significant advantage (, Wilcoxon signed-rank test). These results establish FD magnitude as a key predictor of quantum classification performance, and suggest that near-term quantum machine learning applications in heliophysics should preferentially target high-amplitude space weather events.
Slide 2 of 5 Publicación Acceso Abierto
Women’s scarcity in academic governance. Gendered identity or gendered processes?
(VEZETÉSTUDOMÁNY / BUDAPEST MANAGEMENT REVIEW, 2021-03-31) Solano Cahuana, Iris Laudith
This article contributes to the empirical evidence for women’s scarcity in academic governance. The study evaluates to what extend women lean towards non-management careers and dismiss opportunities to attain executive roles in Colombian public universities, as well as the support received when they break the paradigm. The purpose was to determine
whether gendered practices are ingrained in the designation process or whether women’s scarcity is the outcome of individual attributes/choices and collective perceptions of inadequacy. Data was collected from universities’ proceedings, opinion polls of rectors’ designations, and candidates’ curricula. Findings show low female candidacy rate but high public
support for female candidates to the rector’s seat among all universities examined. Also, curricula’s in-depth analyses display women’s preference for male-dominated careers and analogous academic/administrative experience to that of male candidates. Hence, the results challenge explanations presented by human capital and congruity prejudice theories, while leaning towards gendered processes and identities.
Slide 3 of 5 Publicación Acceso Abierto
Bio-oil and bio-crude gasification for syngas production: energy, exergy and environmental analyses
(ASME, 2026-06-24) Buelvas, Ana; Quintero - Coronel, Daniel A.; Fajardo Cuadro, Juan Gabriel; Barreto Ponton, Deibys; Bula, Antonio; González- Quiroga, Arturo; Grupo de Investigación Energías Alternativas y Fluidos (EOLITO)
Fast pyrolysis is a thermochemical process that converts solid biomass into bio-oil, biochar, and non-condensable gases. In this study, a simulation model was developed in Aspen Plus® using the Ranzi kinetic mechanism to describe biomass pyrolysis. Two gasification pathways were evaluated: bio-oil and bio-crude (a mixture of bio-oil and biochar), employing air and steam as gasifying agents. The Waste Reduction Algorithm was also applied to estimate Potential Environmental Impacts (PEI). Results showed that bio-oil gasification of empty fruit bunches (EFB) achieved higher energy and exergy efficiencies than rice husk (RH). For bio-crude gasification, energy efficiencies reached 50.8% and 44.3% for EFB with air and steam, respectively, while RH achieved 41.1% and 37.7%. Exergy analysis demonstrated that steam gasification improved thermodynamic performance, despite higher energy requirements. For EFB, exergy efficiencies ranged from 64.1% to 70.1% for bio-oil and from 62.9% to 71.9% for bio-crude, whereas RH presented lower efficiencies (53.9%–64.1%) due to its high ash content. Grassmann diagrams indicated that the greatest exergy destruction occurred during combustion and heat transfer, while syngas streams contributed the main exergy gains. Environmental assessment revealed maximum PEI values of 86.5 and 61.2 PEI/h for RH-derived bio-oil using air and steam. Overall, indirect gasification routes appear more efficient and environmentally favorable.
Slide 4 of 5 Publicación Acceso Abierto
TMT Conflict and Innovative Performance: The Moderating Role of Socialization Capabilities and Decision-Making Decentralization
(Revista Brasileira De Gestão De Negócios, 2026-02-27) Del Río Cortina, Jorge Luis; VEGA-JURADO, JAIDER; Prieto Florez, Javier; Grupo de Investigación Centro de Estudios en Negocios e Internacionalización - CENI; Semillero de Investigación en Innovación y Gestión del Conocimiento
Abstract
Purpose – This study aims to analyze the influence of conflict within the top management team (TMT) on innovative performance. It considers the moderating roles of socialization capabilities and decentralized decision-making and addresses
a theoretical and empirical gap in the literature.
Theoretical framework – This study examines the relationship between conflict within the management team and innovative performance. It differentiates between task and relationship conflict and explores the moderating role of socialization
capabilities and decentralization.
Design/methodology/approach – A quantitative approach was adopted to estimate three theoretical models that allow for the evaluation of relationships between conflict in the TMT and innovation. These models are based on data
collected from organizations in various sectors.
Findings – The results show that task conflict positively affects innovative performance, while relationship conflict negatively impacts it.
Practical & social implications of research – To strengthen TMT leadership, it is recommended that programs be implemented to improve interpersonal skills and foster trust and communication. Additionally, adopting decentralized structures
that facilitate innovation is advised.
Originality/value – This study provides a novel approach by analyzing the interaction between internal TMT factors and organizational structural factors.
Keywords: TMT, innovative performance, socialization capabilities, decision-making.
Slide 5 of 5
