A Non-Invasive Technique for Online Defect Detection on Steel Strip Surfaces

During the production of steel strips, a large amount of surface defects can be generated, due to harsh environmental conditions. A high number of surface defects can lead to rejection by the customer, which represents significant economic losses to the production plant. Thus, it is very important to detect the presence and type of the defects generated during the production of each steel strip. Using this information, it is possible to determine whether a strip is suitable for sale, and it may also be useful to determine the origin of defects and, if possible, prevent them from being generated in subsequent strips. To perform these tasks, non-invasive inspection techniques are usually used, carried out automatically by artificial vision systems. Although the inspection conducted by humans is more accurate, they become fatigued quickly, or may even be unable to carry out the inspection correctly when the forward speed of the strip is high. In this paper, a new detection technique is proposed, based on the division of an image into a set of overlapping areas. The optimum values for the configuration parameters of the detection technique are automatically determined using a genetic algorithm. After the detection phase, all the defects are classified using a neural network. A very satisfactory success rate has been achieved in both detection and classification phases.     

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.     

Presence of women on the editorial boards of the language and linguistics journals in Spain

Scientometrics - Many international studies have pointed out the under-representation of women on Editorial Boards of both Science and Social Science journals. Their presence as Editorial Board...     

Non-conventional high-pressure extraction process: A comparative study for astaxanthin recovery from Xanthophyllomyces dendrorhous

Xanthophyllomyces dendrorhous is one of the most attractive natural sources of astaxanthin. The yeast produces the compound intracellularly, therefore, it is necessary to evaluate cell rupture methods using clean and efficient technologies for its extraction and it subsequent use in industries. At present work, two non-conventional high-pressure extraction methods were evaluated for astaxanthin recovery: Supercritical fluid extraction and microfluidisation. Results: Effect of pressure (15, 30, and 45 Megapascals; MPa), Temperature (313 and 343 °K) and usage of co-solvent were studied in supercritical extraction process, meanwhile the effect of microfluidisation process (five stages and 160 MPa) for cell rupture and its combination with conventional technics (lithic enzymes, glass beads and ultrasonication) for the recovery of astaxanthin were evaluated. Supercritical fluid extraction presented a higher astaxanthin recovery, 54% yield extraction, at 32.5 MPa and 313 °K, and using ethanol as co-solvent, compared to a 31% yield extraction by mean microfluidisation process at 160 MPa combined with 15 min of sonication (amplitude of 80%).     

Precooked sorghum flour as proper vehicle of ACE-I and DPP-IV inhibitory sorghum peptides

Sorghum flour was heat treated for producing an instant dispersion ingredient. The precooked sorghum flour was added with ACE-I and DPP-IV inhibitory sorghum peptides (3.0 g peptide 100 g⁻¹). The product was reconstituted in water, and peptide bioaccessibility was evaluated by equilibrium dialysis method after simulated gastrointestinal digestion. Total peptide dialysability of precooked sorghum flour added with sorghum peptides was higher than those obtained for precooked sorghum flour (315.9 ± 14.8 vs. 45.2 ± 5.6 µmol, respectively) (P < 0.05). The ACE-I and DPP-IV-IC₅₀ values of the bioaccessible peptides from the bioactive product were lower than those obtained for precooked sorghum flour ingredient (1.04 ± 0.12 vs. 1.82 ± 0.09 and 0.86 ± 0.02 vs. 2.12 ± 0.08 mg protein mL⁻¹, for ACE-I and DPP-IV, respectively) indicating a higher activity. Precooked sorghum flour was a good vehicle since it did not affect the bioaccessibility of ACE-I and DPP-IV inhibitory peptides provided by sorghum protein hydrolysate.     

Controlling Mechanical Behavior of TWIP Steels by Tuning Texture and Stacking Faults

Metallurgical and Materials Transactions A - We developed an Fe–22Mn–0.6C–1.5Al TWIP steel and investigated how thermo-mechanical processes affect the mechanical properties. In...