Publications by authors named "E Gordo"

The production of green hydrogen through proton exchange membrane water electrolysis (PEMWE) is a promising technology for industry decarbonization, outperforming alkaline water electrolysis (AWE). However, PEMWE requires significant investment, which can be mitigated through material and design advancements. Components like bipolar porous plates (BPPs) and porous transport films (PTFs) contribute substantially to costs and performance.

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The present investigation addresses the mechanical properties, wear behaviour, and high-temperature oxidation of cermets and hardmetals based on either Ti(C,N) or WC and a metal binder based on Fe15Ni or Fe15Ni10Cr. This study also includes a commercial-grade WC-Co for comparative purposes. The production of these materials involved a powder metallurgy and sinter-HIP processing route under identical conditions.

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The present study focuses on the two consecutive and markedly intense Saharan dust intrusion episodes that greatly affected southern Spain (Málaga) and, to a lesser extent, the Canary Islands (Tenerife), in March 2022. These two episodes were the result of atypical meteorological conditions in the region and resulted in record levels of aerosols in the air at the Málaga location. The activity levels of various natural and artificial radionuclides (Be, Pb, K, Cs, Pu, Pu, Pu) and radioactive indicators (gross alpha and gross beta) were impacted by these events and the results are described herein.

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Treatment with second-generation antipsychotics (SGAs) can cause obesity and other cardiometabolic disorders linked to D2 receptor (DRD2) and to genotypes affecting dopaminergic (DA) activity, within reward circuits. We explored the relationship of cardiometabolic alterations with single genetic polymorphisms rs1799732 (NG_008841.1:g.

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Article Synopsis
  • Monthly depositional fluxes of Be, Pb, and K were measured in Southern Spain from 2005 to 2018, and their relationships with atmospheric variables were analyzed using Random Forest and Neural Network machine learning algorithms.
  • Neural Network models showed slightly better predictive performance, with mean Pearson-R coefficients around 0.85, compared to 0.83 for Be, 0.79 for Pb, and 0.8 for K using Random Forest models.
  • The study also used Recursive Feature Elimination to identify the atmospheric variables most correlated with the temporal variability of these radionuclides' depositional fluxes.
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