Effect of the Fiber Size on the Physicochemical and Mechanical Properties of Composites of Epoxy and Date Palm Tree Fibers

Lignocellulosic fibers from date palm trees were employed to reinforce an epoxy matrix. Two fiber sizes were used, with the length and diameter in the range of 20–30 and 1.5–3 mm, respectively, for the so‐called long fibers, and in the range of 5–15 and 0.25–0.75 mm, respectively, for the so‐called short fibers. The morphologies of the resulting composites, as well as their thermal, mechanical, and water sorption properties were evaluated. Strong interactions between both components and etherification reactions may occur between the hydroxyl groups of the fibers and the epoxy groups of the epoxy‐amine reactive mixture. These effects are emphasized when decreasing the size of the fibers.

     

Profiles of volatile compounds in milk containing fish oil analyzed by HS‐SPME‐GC/MS

Long‐chain polyunsaturated fatty acids (LC‐PUFA) have various positive biological effects. Fish oil represents a major source of LC‐PUFA; therefore it is extensively used to enrich food products as, for example, infant formulae, dairy products and fruit juices. However, in the presence of oxygen and metals, LC‐PUFA readily degrade, producing off‐flavors and decreasing the nutritional value of the product. The deterioration of sensory properties (taste and odor) can be easily perceived by the consumer, due to the formation of volatile compounds that are formed by decomposition of lipid hydroperoxides, also known as primary oxidation products. In this study, we used the headspace solid‐phase microextraction‐gas chromatography/mass spectrometry technique (HS‐SPME‐GC/MS) to characterize and quantify volatile compounds in a food matrix supplemented with fish oil. We demonstrated that the HS‐SPME‐GC/MS method is a valuable tool to monitor lipid oxidation at early stages. We identified t‐2‐hexenal and c‐4‐heptenal as possible oxidation markers during the storage of milk enriched with 5% of cod oil.     

Metrological significance of the column test in the assessment of the static segregation of self-compacting concrete in the fresh state

As stated by previous studies, the column test seems to be relevant for the evaluation of the state of segregation of self compacting concrete (SCC) at rest. However, the available information shows a great diversity of apparatus, procedures, aggregate sizes analyzed and segregation indexes. Based on repeatability procedures and statistical analysis of SCC compositions of the French National Project on SCC (PN B@P), this study is aimed particularly at defining what objective sieve size must be chosen to discriminate a real segregation state. When the values of the various indexes proposed in the literature are calculated as a function of sieve size from 2.5 mm, the results show significant variations in the indexes, which are not always explained by a significant segregation in the coarsest aggregate sizes. When segregation does not exist, these variations may be due to a random distribution of the coarsest aggregates. An optimal sieve size D_opt ranging from 0.5.D_max to 0.625.D_max is suggested (D_max, maximum gravel size in the grading curve of concrete) which should ensure correct segregation analysis. In addition trends, but no strong relationships, are noted between the index values calculated from D_opt and the associated criteria.     

Effect of nanoconfinement on the collapse transition of responsive polymer brushes

Nanopatterned brushes of a thermo-responsive polymer, poly(2-(2-methoxyethoxy)ethyl methacrylate) (PMEO2MA), displaying a collapse temperature in the physiological range were synthesized for grafting diameters from a few micrometers down to 35 nm. The reversible collapse transition of the nanobrushes was studied in water as a function of their lateral confinement, down to ensembles of brushes containing only approximately 300 chains. The confinement results in a considerable broadening of the collapse transition and in an increase of the degree of vertical swelling, which can be explained by the internal structure of the nanodroplets derived from a theoretical model of dry nanobrushes. These results enable the rational design of responsive surfaces having a tunable topography engineered at the nanometer scale, which is of direct interest for the development of soft nanoactuators and new substrates for cell adhesion studies.     

Mechanical performance curves for the strength grading of maritime pine

Finite element models (FEM) were used to simulate beam sections in bending with a knot. They aim at evaluating the mechanical behaviour of timber considering the effect of this singularity on resulting bending strength. By using linear elastic theory and an adapted failure criterion (Tsaï–Hill), an equivalent state can be deduced, giving information about the influence of knot on the load bearing capacity of the element. Several 2D-FEM were then developed using the free software Castem^® by considering plane strain. The beam section was considered like a composite material with two materials; the wood and the knot. The slope of grain around the defect was implemented by using a simple exponential equation parameterized as a function of the radius of the singularity. The location and the size of the defect and the longitudinal modulus of elasticity of wood were investigated in this study. Results exhibit performance curves specific to bending strength. These numerical performance curves were not used to predict the bending strength but to identify some thresholds, function of the size and the location of a critical knot and the stiffness of structural beams. 188 beams with a length of 4.5 m and a cross-section of 200?×?100 mm² were tested to study the efficiency of numerical thresholds. This study shows that it is possible, by identifying only the geometrical properties of the critical defect and the stiffness of the structural beam, to improve the prediction of the bending strength of beams with a large cross-section in Maritime pine up to C40.     

Molecular Identification of Endophytic Bacteria in Leucojum aestivum In Vitro Culture,NMR-Based Metabolomics Study and LC-MS Analysis Leading to Potential Amaryllidaceae Alkaloid Production

In this study, endophytic bacteria belonging to the Bacillus genus were isolated from in vitro bulblets of Leucojum aestivum and their ability to produce Amaryllidaceae alkaloids was studied. Proton Nuclear Magnetic Resonance (¹H NMR)-based metabolomics combined with multivariate data analysis was chosen to compare the metabolism of this plant (in vivo bulbs, in vitro bulblets) with those of the endophytic bacteria community. Primary metabolites were quantified by quantitative ¹H NMR (qNMR) method. The results showed that tyrosine, one precursor of the Amaryllidaceae alkaloid biosynthesis pathway, was higher in endophytic extract compared to plant extract. In total, 22 compounds were identified including five molecules common to plant and endophyte extracts (tyrosine, isoleucine, valine, fatty acids and tyramine). In addition, endophytic extracts were analyzed using Liquid Chromatography-Mass Spectrometry (LC-MS) and Gas Chromatography-Mass Spectrometry (GC-MS) for the identification of compounds in very low concentrations. Five Amaryllidaceae alkaloids were detected in the extracts of endophytic bacteria. Lycorine, previously detected by ¹H NMR, was confirmed with LC-MS analysis. Tazettine, pseudolycorine, acetylpseudolycorine, 1,2-dihydro-chlidanthine were also identified by LC-MS using the positive ionization mode or by GC-MS. In addition, 11 primary metabolites were identified in the endophytic extracts such as tyramine, which was obtained by decarboxylation of tyrosine. Thus, Bacillus sp. isolated from L. aestivum bulblets synthesized some primary and specialized metabolites in common with the L. aestivum plant. These endophytic bacteria are an interesting new approach for producing the Amaryllidaceae alkaloid such as lycorine.     

Understanding the Initial Solidification Behavior for Al–Si Alloy in Cold Chamber High-Pressure Die Casting (CC-HPDC) Process Combining Experimental and Modeling Approach

Metallurgical and Materials Transactions A - In the cold chamber high-pressure die casting (CC-HPDC) process, alloy solidification in the shot sleeve due to heat loss leads to the formation of...     

Wasserstein discriminant analysis

Wasserstein discriminant analysis (WDA) is a new supervised linear dimensionality reduction algorithm. Following the blueprint of classical Fisher Discriminant Analysis, WDA selects the projection matrix that maximizes the ratio of the dispersion of projected points pertaining to different classes and the dispersion of projected points belonging to a same class. To quantify dispersion, WDA uses regularized Wasserstein distances. Thanks to the underlying principles of optimal transport, WDA is able to capture both global (at distribution scale) and local (at samples’ scale) interactions between classes. In addition, we show that WDA leverages a mechanism that induces neighborhood preservation. Regularized Wasserstein distances can be computed using the Sinkhorn matrix scaling algorithm; the optimization problem of WDA can be tackled using automatic differentiation of Sinkhorn’s fixed-point iterations. Numerical experiments show promising results both in terms of prediction and visualization on toy examples and real datasets such as MNIST and on deep features obtained from a subset of the Caltech dataset.     

Flowering as the Most Highly Sensitive Period of Grapevine (Vitis vinifera L. cv Mourvèdre) to the Botryosphaeria Dieback Agents Neofusicoccum parvum and Diplodia seriata Infection

Botryosphaeria dieback is a fungal grapevine trunk disease that currently represents a threat for viticulture worldwide because of the important economical losses due to reduced yield of affected plants and their premature death. Neofusicoccum parvum and Diplodia seriata are among the causal agents. Vine green stems were artificially infected with N. parvum or D. seriata at the onset of three different phenological stages (G stage (separated clusters), flowering and veraison). Highest mean lesion lengths were recorded at flowering. Major proteome changes associated to artificial infections during the three different phenological stages were also reported using two dimensional gel electrophoresis (2D)-based analysis. Twenty (G stage), 15 (flowering) and 13 (veraison) differentially expressed protein spots were subjected to nanoLC-MS/MS and a total of 247, 54 and 25 proteins were respectively identified. At flowering, a weaker response to the infection was likely activated as compared to the other stages, and some defense-related proteins were even down regulated (e.g., superoxide dismutase, major latex-like protein, and pathogenesis related protein 10). Globally, the flowering period seemed to represent the period of highest sensitivity of grapevine to Botryosphaeria dieback agent infection, possibly being related to the high metabolic activity in the inflorescences.