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Safety-factor dataset for high embankments determined with different analytical methods.

ABSTRACT: Slope-stability analysis is one of the parameters in the design of road embankments that the designer must consider in order to ensure stable and safe construction. The technical standards recommend slopes to heights of 12 m, depending on the soil types and the topography. In the present work, the limit equilibrium methods (Fellenius, Bishop, Janbu, Morgensten-Price) and the finite element method are used to determine the safety factor of road embankments for different slopes flanking the road. Five embankment heights were simulated: 6 m, 12 m, 18 m, 24 m, and 30 m. The dataset compiled can be used for modeling embankments.

SUBMITTER: Mesa-Lavista M

PROVIDER: S-EPMC8403731 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Safety-factor dataset for high embankments determined with different analytical methods.

Mesa-Lavista Milena M Álvarez-Pérez José J Tejeda-Piusseaut Eduardo E Lamas-Fernández Francisco F

Data in brief 20210822

Slope-stability analysis is one of the parameters in the design of road embankments that the designer must consider in order to ensure stable and safe construction. The technical standards recommend slopes to heights of 12 m, depending on the soil types and the topography. In the present work, the limit equilibrium methods (Fellenius, Bishop, Janbu, Morgensten-Price) and the finite element method are used to determine the safety factor of road embankments for different slopes flanking the road. ...[more]

PMID: 34485645

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Project description:Dissolution of inhaled engineered nanomaterials (ENM) under physiological conditions is essential to predict the clearance of the ENM from the lungs and to assess their biodurability and the potential effects of released ions. Alveolar macrophage (AM) lysosomes contain a pH 4.5 saline brine with enzymes and other components. Different types of artificial phagolysosomal simulant fluids (PSFs) have been developed for dissolution testing, but the consequence of using different media is not known. In this study, we tested to which extent six fundamentally different PSFs affected the ENM dissolution kinetics and particle size as determined by a validated transmission electron microscopy (TEM) image analysis. Three lysosomal simulant media were consistent with each other and with in vivo clearance. These media predict the quick dissolution of ZnO, the partial dissolution of SiO2, and the very slow dissolution of TiO2. The valid media use either a mix of organic acids (with the total concentration below 0.5 g/L, thereof citric acid below 0.15 g/L) or another organic acid (KH phthalate). For several ENM, including ZnO, BaSO4, and CeO2, all these differences induce only minor modulation of the dissolution rates. Only for TiO2 and SiO2, the interaction with specific organic acids is highly sensitive, probably due to sequestration of the ions, and can lead to wrong predictions when compared to the in vivo behavior. The media that fail on TiO2 and SiO2 dissolution use citric acid at concentrations above 5 g/L (up to 28 g/L). In the present selection of ENM, fluids, and methods, the different lysosomal simulant fluids did not induce changes of particle morphology, except for small changes in SiO2 and BaSO4 particles most likely due to ion dissolution, reprecipitation, and coalescence between neighboring particles. Based on the current evidence, the particle size by TEM analysis is not a sufficiently sensitive analytical method to deduce the rate of ENM dissolution in physiological media. In summary, we recommend the standardization of ENM dissolution testing by one of the three valid lysosomal simulant fluids with determination of the dissolution rate and halftime by the quantification of ions. This recommendation was established for a continuous flow system but may be relevant as well for static (batch) solubility testing.

Project description:BackgroundWhite rot fungi have been used to improve the nutritive value of lignocellulose for ruminants. In feed analysis, the Van Soest method is widely used to determine the cell wall contents. To assess the reliability of this method (Method A) for determination of cell wall contents in fungal-treated wheat straw, we compared a combined monosaccharide analysis and pyrolysis coupled to gas chromatography with mass spectrometry (Py-GC/MS) (Method B). Ruminal digestibility, measured as in vitro gas production (IVGP), was subsequently used to examine which method explains best the effect of fungal pretreatment on the digestibility of wheat straw.ResultsBoth methods differed considerably in the mass recoveries of the individual cell wall components, which changed on how we assess their degradation characteristics. For example, Method B gave a higher degradation of lignin (61.9%), as compared to Method A (33.2%). Method A, however, showed a better correlation of IVGP with the ratio of lignin to total structural carbohydrates, as compared to Method B (Pearson's r of -0.84 versus -0.69). Nevertheless, Method B provides a more accurate quantification of lignin, reflecting its actual modification and degradation. With the information on the lignin structural features, Method B presents a substantial advantage in understanding the underlying mechanisms of lignin breakdown. Both methods, however, could not accurately quantify the cellulose contents - among others, due to interference of fungal biomass.ConclusionMethod A only accounts for the recalcitrant residue and therefore is more suitable for evaluating ruminal digestibility. Method B allows a more accurate quantification of cell wall, required to understand and better explains the actual modification of the cell wall. The suitability of both methods, therefore, depends on their intended purposes. © 2019 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Project description:Aspergillus fumigatus biofilms represent a problematic clinical entity, especially because of their recalcitrance to antifungal drugs, which poses a number of therapeutic implications for invasive aspergillosis, the most difficult-to-treat Aspergillus-related disease. While the antibiofilm activities of amphotericin B (AMB) deoxycholate and its lipid formulations (e.g., liposomal AMB [LAMB]) are well documented, the effectiveness of these drugs in combination with nonantifungal agents is poorly understood. In the present study, in vitro interactions between polyene antifungals (AMB and LAMB) and alginate lyase (AlgL), an enzyme degrading the polysaccharides produced as extracellular polymeric substances (EPSs) within the biofilm matrix, against A. fumigatus biofilms were evaluated by using the checkerboard microdilution and the time-kill assays. Furthermore, atomic force microscopy (AFM) was used to image and quantify the effects of AlgL-antifungal combinations on biofilm-growing hyphal cells. On the basis of fractional inhibitory concentration index values, synergy was found between both AMB formulations and AlgL, and this finding was also confirmed by the time-kill test. Finally, AFM analysis showed that when A. fumigatus biofilms were treated with AlgL or polyene alone, as well as with their combination, both a reduction of hyphal thicknesses and an increase of adhesive forces were observed compared to the findings for untreated controls, probably owing to the different action by the enzyme or the antifungal compounds. Interestingly, marked physical changes were noticed in A. fumigatus biofilms exposed to the AlgL-antifungal combinations compared with the physical characteristics detected after exposure to the antifungals alone, indicating that AlgL may enhance the antibiofilm activity of both AMB and LAMB, perhaps by disrupting the hypha-embedding EPSs and thus facilitating the drugs to reach biofilm cells. Taken together, our results suggest that a combination of AlgL and a polyene antifungal may prove to be a new therapeutic strategy for invasive aspergillosis, while reinforcing the EPS as a valuable antibiofilm drug target.

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Safety-factor dataset for high embankments determined with different analytical methods.

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Safety-factor dataset for high embankments determined with different analytical methods.

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