The Influence of Cu\u3csub\u3e3\u3c/sub\u3e(BTC)\u3csub\u3e2\u3c/sub\u3e metal organic framework on the permeability and perm-selectivity of PLLA-MOF mixed matrix membranes

Poly(l-lactic acid) (PLLA) - 20% (w/w) and Cu3(BTC)2 metal organic framework (MOF) based mixed matrix membranes (MMMs) were fabricated by a vertical corotating twin screw microcompounder followed by an injection molding process. Water vapor, CO2, O2, and selected aroma mass transfer properties of PLLA and PLLA MMMs were evaluated. The CO2/O2 perm-selectivity of PLLA (αCO2/O2) MMMs increased from 7.6 to 10.3 with the incorporation of 20% Cu3(BTC)2 MOF. Gravimetric permeability studies of trans-2-hexenal performed at 23°C and 50% RH indicated that permeability coefficient of PLLA MMMs increased by around 60% as compared to regular PLLA film. However, no changes in mass transfer rates were observed for acetaldehyde. Furthermore, the thermal processing parameters as well as the presence of MOF did not show any significant effect on the molecular weight of the PLLA matrix nor on the crystalline structure of the Cu3(BTC)2 MOF, which was confirmed by both gel permeation chromatography and X-ray diffraction studies

Το λογισμικό SpatialAnalyzer & εφαρμογές του σε προβλήματα βιομηχανικής γεωδαισίας

This paper reports a first study exploring genomic prediction for adaptation of sorghum [Sorghum bicolor (L.) Moench] to drought-stress (D-ET) and nonstress (W-ET) environment types. The objective was to evaluate the impact of both modeling genotype × environment interaction (G×E) and accounting for heterogeneous variances of marker effects on genomic prediction of parental breeding values for grain yield within and across environment types (ETs). For this aim, different genetic covariance structures and different weights for individual markers were investigated in best linear unbiased prediction (BLUP)-based prediction models. The BLUP models used a kinship matrix combining pedigree and genomic information, termed K-BLUP. The dataset comprised testcross yield performances under D-ET and W-ET as well as pedigree and genomic data. In general, modeling G×E increased predictive ability and reduced empirical bias of genomic predictions for broad adaptation across both ETs vs. models that ignored G×E by fitting a main genetic effect only. Genomic predictions for specific adaptation to D-ET or W-ET were also improved by K-BLUP models that explicitly accommodated G×E and used data from both ETs relative to prediction models that used data from the targeted ET exclusively or models that used all the data but assumed no G×E. Allowing for heterogeneous marker variances through weighted K-BLUP produced clear increments (43–72%) in predictive ability of genomic prediction for grain yield in all adaptation scenarios. We conclude that G×E as well as locus-specific genetic variances should be accommodated in genomic prediction models to improve adaptability of sorghum to variable environmental conditions

In Situ Compatibilization of Biopolymer Ternary Blends by Reactive Extrusion with Low-Functionality Epoxy-Based Styrene Acrylic Oligomer

[EN] The present study reports on the use of low-functionality epoxy-based styrene¿acrylic oligomer (ESAO) to compatibilize immiscible ternary blends made of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), polylactide (PLA), and poly(butylene adipate-co-terephthalate) (PBAT). The addition during melt processing of low-functionality ESAO at two parts per hundred resin (phr) of biopolymer successfully changed the soften inclusion phase in the blend system to a thinner morphology, yielding biopolymer ternary blends with higher mechanical ductility and also improved oxygen barrier performance. The compatibilization achieved was ascribed to the in situ formation of a newly block terpolymer, i.e. PHBVb- PLA-b-PBAT, which was produced at the blend interface by the reaction of the multiple epoxy groups present in ESAO with the functional terminal groups of the biopolymers. This chemical reaction was mainly linear due to the inherently low functionality of ESAO and the more favorable reactivity of the epoxy groups with the carboxyl groups of the biopolymers, which avoided the formation of highly branched and/or cross-linked structures and thus facilitated the films processability. Therefore, the reactive blending of biopolymers at different mixing ratios with low-functionality ESAO represents a straightforward methodology to prepare sustainable plastics at industrial scale with different physical properties that can be of interest in, for instance, food packaging applications.This research was funded by the EU H2020 project YPACK (Reference number 773872) and by the Spanish Ministry of Science, Innovation, and Universities (MICIU) with project numbers MAT2017-84909-C2-2-R and AGL2015-63855-C2-1-R. L. Quiles-Carrillo wants to thank the Spanish Ministry of Education, Culture, and Sports (MECD) for financial support through his FPU Grant Number FPU15/03812. Torres-Giner also acknowledges the MICIU for his Juan de la Cierva contract (IJCI-2016-29675).Quiles-Carrillo, L.; Montanes, N.; Lagaron, J.; Balart, R.; Torres-Giner, S. (2019). In Situ Compatibilization of Biopolymer Ternary Blends by Reactive Extrusion with Low-Functionality Epoxy-Based Styrene Acrylic Oligomer. 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Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts

Consolidation process boundaries of the degradation of mechanical properties in compression moulding of natural-fibre bio-polymer composites

In spite of the volume of literature on natural fibres, bio-matrix materials and their composites, the choices of optimum process parameters such as moulding temperature, pressure and compression time are still largely based on experience, rules of thumb and general knowledge of the chemical and physical processes occurring in the melt during consolidation. The moulding process itself is a complex balance between processes that must occur for the composite to successfully consolidate and the onset of thermal degradation of the natural fibre and/or matrix materials. This paper brings together models of thermal penetration, melt infusion, thermal degradation and chemical degradation of natural polymers to construct an ideal processing window for a bio-composite. All processes are mapped in terms of normalized consolidation progress parameters making it easier to identify critical processes and process boundaries. Validation of the concept is achieved by measuring changes in the mechanical properties of a flax/PLA bio-composite formed over a range of processing conditions within and outside of the optimized window

Aspekte einer Sprachendidaktik in wirtschaftswissenschaftlichen Masterstudiengängen : eine empirische Studie am Beispiel der englischen Sprache

Die vorliegende Arbeit ist das Ergebnis meiner Beschäftigung im Bereich des Content and Language Integrated Learning und erster Einblicke in international agierende Firmen, deren Mitarbeiter im globalen Wirtschaftsraum mehr und mehr fundierte fremdsprachliche Kenntnisse besitzen müssen. Dieser motivationale Antrieb führte zur intensiven Auseinandersetzung mit den speziellen Studienmöglichkeiten im Masterbereich, die bislang nur marginal untersucht wurden

Usefulness Criterion and Post-selection Parental Contributions in Multi-parental Crosses: Application to Polygenic Trait Introgression

Predicting the usefulness of crosses in terms of expected genetic gain and genetic diversity is of interest to secure performance in the progeny and to maintain long-term genetic gain in plant breeding. A wide range of crossing schemes are possible including large biparental crosses, backcrosses, four-way crosses, and synthetic populations. In silico progeny simulations together with genome-based prediction of quantitative traits can be used to guide mating decisions. However, the large number of multi-parental combinations can hinder the use of simulations in practice. Analytical solutions have been proposed recently to predict the distribution of a quantitative trait in the progeny of biparental crosses using information of recombination frequency and linkage disequilibrium between loci. Here, we extend this approach to obtain the progeny distribution of more complex crosses including two to four parents. Considering agronomic traits and parental genome contribution as jointly multivariate normally distributed traits, the usefulness criterion parental contribution (UCPC) enables to (i) evaluate the expected genetic gain for agronomic traits, and at the same time (ii) evaluate parental genome contributions to the selected fraction of progeny. We validate and illustrate UCPC in the context of multiple allele introgression from a donor into one or several elite recipients in maize (Zea mays L.). Recommendations regarding the interest of two-way, three-way, and backcrosses were derived depending on the donor performance. We believe that the computationally efficient UCPC approach can be useful for mate selection and allocation in many plant and animal breeding contexts