Development of a novel device for applying uniform doses of electron beam irradiation on carcasses

The Maxim's Electron Scatter Chamber (Maxim Chamber) was developed to obtain uniform dose distribution when applying electron beam (e-beam) irradiation to materials of irregular surface. This was achieved by placing a stainless steel mesh surrounding a cylindrical area where the target sample was placed. Upon contact with the mesh, electrons scatter and are directed onto the target from multiple angles, eliminating the e-beam linearity and resulting in a uniform dose distribution over the target surface. The effect of irradiation in the Maxim Chamber on dose distribution and pathogen reduction was tested on rabbit carcasses to simulate other larger carcasses. The dose uniformity ratio (DUR) on the rabbit carcasses was 1.8, indicating an acceptable dose distribution. On inoculated carcasses, this treatment reduced Escherichia coli O157:H7 by > 5 log cycles. These results indicate that carcass irradiation using e-beam is feasible using the Maxim's electron scattering chamber. Appropriate adjustments will be further needed for commercial application on beef and other animal carcasses.     

Anisotropic diffusion of hydrogen in nanoporous carbons

It is accepted that hydrogen transport capacity through carbons depends on the anisotropy of the empty spaces that constitute their porous structure. However, very little is known about this relationship. Computational simulation is an excellent tool to accomplish this kind of studies. Simulation requires digital representations of materials and a model describing the interaction potential among the gas molecules and the solids surfaces. In this work, it is proposed to use the analytical solutions of the truncated pore problem for modeling the potentials, and an immiscible lattice gas for obtaining the representations. The degree of anisotropy was quantified by using the mean intercept length method. The adsorption isotherms and the self-diffusion coefficients in the three orthogonal directions were found by the grand canonical and kinetic Monte Carlo methods, respectively. The results suggest the existence of a gas pressure at which a molecular saturation threshold (P _s) is reached. P _s determines if the degree of anisotropy is or not a representative variable of diffusive transport. For P ≤ P _s, the degree of anisotropy favors the molecular mobility. When P > P _s, the degree of anisotropy loses influence on mobility.     

Effect of rheology and humic acids on the transport of environmental fluids: Potential implications for soil remediation revealed through microfluidics

This study investigated the potential effect of shear rheology and humic acids (HA) on the subsurface transport of polymeric fluids used for the remediation of contaminants. Polymeric fluids were prepared with guar, scleroglucan, and carboxymethyl cellulose (CMC). Guar fluids can be used to suspend reactive particles for contaminant degradation. Fluids prepared with 2.5 g/L of guar in water were viscous, and the crosslinker borax (1 g/L) made them viscoelastic. Microfluidics experiments showed that the increase in elasticity blocked the flow of guar in 350 μm channels. Guar, CMC, or scleroglucan fluids containing sodium thiosulfate can be used to trap toxic Cr(VI) in the subsurface and reduce it to harmless Cr(III). Trapping of Cr(VI) is achieved by the gelation of the fluids upon contact with chromium. Before mixing with chromium, HA did not affect the flow of CMC, guar, and scleroglucan in microfluidic channels. Quartz-crystal microbalance with dissipation monitoring experiments indicates that HA reduced sorption of guar onto silica, potentially promoting the transport of guar fluids in sandy aquifers. While HA slightly decreased the rate of gelation of CMC and scleroglucan upon contact with chromium, it did not affect the fast gelation rate of guar. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48465.     

Analytical Solutions to Predict Impact Behaviour of Stringer Stiffened Composite Aircraft Panels

Applied Composite Materials - This paper aims to develop an analytical method to predict the low-velocity impact response of simply supported stringer stiffened panels. Since the combination of...     

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.     

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%).     

Statistical analysis of a multi-objective optimization algorithm based on a model of particles with vorticity behavior

In this paper, a strategy for multi-objective optimization based upon the behavior of a particle swarm with rotational and linear motion is presented. The strategy for multi-objective optimization is based upon the emulation of the linear and circular movements of a swarm (flock). Thus emerges the physical basis for the cognitive model, which in conjunction with exploration–exploitation results in the proposal of a cognitive algorithm, which is tested through several multi-objective optimization functions. The algorithm proposed is compared with standard particle swarm optimization multi-objective via statistical analysis.