Pentadecane functionalized graphite oxide sheets as a tool for the preparation of electrical conductive polyethylene/graphite oxide composites

Covalent functionalization of pentadecane-decorated thermally reduced graphite oxide (GO) sheets has been studied as a tool for the preparation of polyethylene/GO composites exhibiting rheological and electrical percolation thresholds. It was accomplished through pentadecane based radical addition onto unsaturated bonds located on the GO sheets' surface using dicumyl peroxide as hydrogen abstractor. This chemical functionalization influences the affinity of the formed pentadecane grafted GO sheets for various solvents. Then, the compounding of the composites pentadecane grafted GO/PE was performed at a processing temperature of 140 °C with 25, 20, 15, 10, 8 and 5 wt% loadings. Rheological and electrical percolation thresholds were found between 10 and 15 wt% for polyethylene/pentadecane functionalized graphene oxide composites while the composite graphite/PE at the same loading percentage did not reach any percolation threshold.     

Dispersive mixing efficiency of an elongational flow mixer on PP/EPDM blends: Morphological analysis and correlation with viscoelastic properties

Polypropylene and ethylene‐propylene‐diene terpolymer (PP/EPDM) blends were melt compounded in a new mixing device, designed in our laboratory under the trademark of RMX®, which predominantly generates elongational flows. Dispersion of the EPDM minor phase in PP was carried out in both RMX® and in an internal mixer (Haake Rheomix 600) at equivalent specific mixing energies and the resultant morphologies obtained by SEM were analyzed and compared. A better dispersive mixing efficiency of the RMX® mixer, i.e., lower D_n and D_v of the dispersed EPDM phase was observed. The impact of elongational flow was more pronounced for blends having a high viscosity ratio p, indicating an enhanced droplet break‐up mechanism, which was attributed to the combination of high shear rates inside the mixing element and important elongational flows in the convergent/divergent zones. The morphology of the blends was correlated with their linear viscoelastic properties by using the Palierne model. Very good agreement was found for the PP/EPDM 80/20 blends but for higher EPDM content, the Palierne model failed to describe the rheological behavior, which was attributed to percolation of the minor phase with increasing the concentration. Higher elasticity at low frequencies was observed for blends processed in the RMX®, which was attributed to a higher generated interfacial area. POLYM. ENG. SCI., 54:1444–1457, 2014. © 2013 Society of Plastics Engineers     

Role of Methyl Salicylate on Oviposition Deterrence in Arabidopsis thaliana

Plants attacked by herbivores have evolved different strategies that fend off their enemies. Insect eggs deposited on leaves have been shown to inhibit further oviposition through visual or chemical cues. In some plant species, the volatile methyl salicylate (MeSA) repels gravid insects but whether it plays the same role in the model species Arabidopsis thaliana is currently unknown. Here we showed that Pieris brassicae butterflies laid fewer eggs on Arabidopsis plants that were next to a MeSA dispenser or on plants with constitutively high MeSA emission than on control plants. Surprisingly, the MeSA biosynthesis mutant bsmt1-1 treated with egg extract was still repellent to butterflies when compared to untreated bsmt1-1. Moreover, the expression of BSMT1 was not enhanced by egg extract treatment but was induced by herbivory. Altogether, these results provide evidence that the deterring activity of eggs on gravid butterflies is independent of MeSA emission in Arabidopsis, and that MeSA might rather serve as a deterrent in plants challenged by feeding larvae.     

Effect of iron chelates on oil–water interface,stabilized by milk proteins: The role of phosphate groups and pH. Prediction of iron transfer from aqueous phase toward fat globule surface by changes of interfacial properties

Iron incorporated into food systems induces oxidation and precipitation. The consequences are reduced bioavailability and a functional modification of other food components such as proteins. The iron-chelates such as ferrous bisglycinate represent a possibility to avoid side effects, since the iron is protected. The aim of this study is to investigate the effects of iron-chelates compounds on the properties of an oil/water interface stabilized by caseinate or β-lacotoglobulin, under environmental conditions at 20 °C. Analyses were performed using dynamic drop tensiometry during 5000 s. The aqueous bulk phase is an imidazole/acetate buffer (0.1 M), containing 0.4 × 10⁻⁶ M protein, and 0.2 × 10^-6 9 M iron-chelates compounds. The results indicate that, under neutral conditions, the addition of some irons salts (NaFe-EDTA or Fe-bisglycinate) do not change the structure of the interface stabilized by a protein containing no phosphate groups (β-lactoglobulin). In the case of caseinate, NaFe-EDTA addition increases the lowering rate of surface tension at pH 6.5. On the contrary, the lowering rate of surface tension with caseinate is inhibited by Fe-bisglycinate at pH 6.5. Such an effect is not observed with β-lactoglobulin. The low transfer of irons ions from the bulk to the interface stabilized by β-lactoglobulin is confirmed by zetameter and FTIR measurements. These results indicate an effective strategy to follow for controlling the physical and chemical stability of an emulsion stabilized with proteins.     

Co-creation of value and the project context: Towards application on the case of Hinkley Point C Nuclear Power Station

The research analyses decisions as evaluative outcomes regarding project value. The UK-French Hinkley Point C Nuclear Power Station provides the case study. Value is traditionally assessed as inputs and outputs. Here, value is conceptualized as a co-created value proposition at the front-end with implications for realization post-completion. Service-dominant logic (SDL) provides the theoretical lens and contributes to a methodological approach for examining projects. Decision-making outcomes provide the evidence from a range of data sources, including reports and commentaries. The methods are interpretative. The findings show that decision-making extends beyond the time-cost-quality/scope dimensions. The long-term issues regarding value realized are often overlooked. Stakeholders and individual actors have mainly focused upon managing political and financial risks, especially time and cost. The research poses challenges to project management analysis, SDL and research design in assessing evidence. Addressing these issues facilitates a knowledge contribution to SDL theorization and the field of project management.     

A decomposition theorem for finite persistent transition systems

In this paper, we consider finite labelled transition systems. We show that if such transition systems are deterministic, persistent, and weakly periodic, then they can be decomposed in the following sense. There exists a finite set of label-disjoint cycles such that any other cycle is Parikh-equivalent to a multiset of cycles from this set.     

You Are What You Read

Given that useful knowledge in software engineering has a half-life of about five years, reading remains an excellent way to replenish this vanishing resource for the diligent software engineer.     

Clustering sensor data for autonomous terrain identification using time-dependency

In this paper we are interested in autonomous vehicles that can automatically develop terrain classifiers without human interaction or feedback. A key issue is the clustering of time-series data collected by the sensors of a ground-based vehicle moving over several terrain surfaces (e.g. concrete or soil). In this context, we present a novel off-line windowless clustering algorithm that exploits time-dependency between samples. In terrain coverage, sets of sensory measurements are returned that are spatially, and hence temporally, correlated. Our algorithm works by finding a set of parameter values for a user-specified classifier that minimize a cost function. This cost function is related to the change in classifier probability estimates over time. The main advantage over other existing methods is its ability to cluster data for fast-switching systems that either have high process or observation noise, or complex distributions that cannot be properly characterized within the time interval that the system stays in a single state. The algorithm was evaluated using three different classifiers (linear separator, mixture of Gaussians and k-Nearest Neighbor), over both synthetic data sets and two different mobile robotic platforms, with success. Comparisons are provided against a window-based algorithm and against a hidden Markov model trained with Expectation-Maximization, with positive results.