Incorporating amylopectin in poly(lactic acid) by melt blending using poly(ethylene‐co‐vinyl alcohol) as a thermoplastic carrier. (I) morphological characterization

In this study, the possibility of using a biodegradable grade of thermoplastic poly(ethylene‐co‐vinyl alcohol) with high (71 mol %) vinyl alcohol (EVOH‐29), as a carrier to incorporate the renewable and biodegradable component amylopectin (AP) into poly(lactic acid) (PLA) through melt blending, was investigated. The effect of using a plasticizer/compatibilizer (glycerol) in the blend systems was also investigated. In a first step, the EVOH/AP blends were produced and thereafter, in a second step, these were mixed with PLA. In this first study, the blend morphology was investigated using optical microscopy, scanning electron microscopy and Raman imaging spectroscopy and the thermal properties were measured by differential scanning calorimetry. Despite the fact that EVOH and AP are both highly polar, their blends were immiscible. Still, the blends exhibited an excellent phase dispersion on a micron level, which was enhanced further by the addition of glycerol. A good phase dispersion was finally observed by incorporation of the latter blends in the PLA matrix, suggesting that the proposed blending route can be successfully applied for these systems. Finally, the Differential scanning calorimetry (DSC) data showed that the melting point of EVOH dropped in the EVOH/AP blends, but the properties of the PLA phase was still relatively unaffected as a result of blending with the above components. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Biobased composites prepared by compression molding with a novel thermoset resin from soybean oil and a natural‐fiber reinforcement

Biobased composites were manufactured with a compression‐molding technique. Novel thermoset resins from soybean oil were used as a matrix, and flax fibers were used as reinforcements. The air‐laid fibers were stacked randomly, the woven fabrics were stacked crosswise (0/90°), and impregnation was performed manually. The fiber/resin ratio was 60 : 40. The prepared biobased composites were characterized by impact and flexural testing. Scanning electron microscopy of knife‐cut cross sections of the specimens was also done to investigate the fiber–matrix interface. Thermogravimetric analysis of the composites was carried out to provide indications of thermal stability. Three resins from soybean oil [methacrylated soybean oil, methacrylic anhydride modified soybean oil (MMSO), and acetic anhydride modified soybean oil] were used as matrices. The impact strength of the composites with MMSO resin reinforced with air‐laid flax fibers was 24 kJ/m², whereas that of the MMSO resin reinforced with woven flax fabric was between 24 and 29 kJ/m². The flexural strength of the MMSO resin reinforced with air‐laid flax fibers was between 83 and 118 MPa, and the flexural modulus was between 4 and 6 GPa, whereas the flexural strength of the MMSO resin reinforced with woven fabric was between 90 and 110 MPa, and the flexural modulus was between 4.87 and 6.1 GPa. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Novel Foams Based on Freeze‐Dried Renewable Vital Wheat Gluten

A new way of producing rigid or semi‐rigid foams from vital wheat gluten using a freeze‐drying process is reported. Water/gluten‐based mixtures were frozen and freeze‐dried. Different foam structures were obtained by varying the mixing process and wheat gluten concentration, or by adding glycerol or bacterial cellulose nanofibers. MIP revealed that the foams had mainly an open porosity peaking at 93%. The average pore diameter ranged between 20 and 73 µm; the sample with the highest wheat gluten concentration and no plasticizer had the smallest pores. Immersion tests with limonene revealed that the foams rapidly soaked up the liquid. An especially interesting feature of the low‐wheat‐concentration foams was the “in situ” created soft‐top‐rigid‐bottom foams.

     

Modification of Substrate Specificity Resulting in an Epoxide Hydrolase with Shifted Enantiopreference for (2,3‐Epoxypropyl)benzene

Random mutagenesis targeted at hotspots of noncatalytic active‐site residues of potato epoxide hydrolase StEH1 combined with an enzyme‐activity screen allowed the isolation of enzyme variants displaying altered enantiopreference in the catalyzed hydrolysis of (2,3‐epoxypropyl)benzene. The wild‐type enzyme favored the S enantiomer with a ratio of 2.5:1, whereas the variant displaying the most radical functional changes showed a 15:1 preference for the R enantiomer. This mutant had accumulated four substitutions distributed over two out of four mutated hotspots: W106L, L109Y, V141K, and I151V. The underlying causes of the enantioselectivity were a decreased catalytic efficiency in the catalyzed hydrolysis of the S enantiomer combined with retained activity with the R enantiomer. The results demonstrate the feasibility of molding the stereoselectivity of this biocatalytically relevant enzyme.     

Chemical images

Chemical sensors can be used to generate a vast amount of information about the emissions from bio- and chemical processes, from food and bacteria and from a number of products. These emissions are either wanted or should be avoided. Wolfgang Göpel was one of those who recognized early the large potential of chemical sensor arrays and different modes of operation of a given sensor. We describe how large area field effect devices, with catalytic metal gates, can be used for the construction of a response image of a gaseous emission. More specifically, we discuss the new possibilities obtained through the use of catalytic metals with a gradient in thickness. Some basic features of such sensing surfaces are demonstrated and, finally, time-dependent response images from aging meat are used to demonstrate the potential of the method used. It is based on a scanning light pulse technique (SLPT) which measures local polarization or work function changes in two dimensions and, e.g. a sensing surface consisting of bands of different catalytic metals with a gradient in thickness.     

Robust load balancing under traffic uncertainty��tractable models and efficient algorithms

Routing configurations that have been optimized for a nominal traffic scenario often display significant performance degradation when they are subjected to real network traffic. These degradations are due to the inherent sensitivity of classical optimization techniques to changes in model parameters combined with the significant traffic variations caused by demand fluctuations, component failures and network reconfigurations. In this paper, we review important sources for traffic variations in data networks and describe tractable models for capturing the associated traffic uncertainty. We demonstrate how robust routing settings with guaranteed performance for all foreseen traffic variations can be effectively computed via memory efficient iterative techniques and polynomial-time algorithms. The techniques are illustrated on real data from operational IP networks.     

Distortion of Norway spruce timber Part 2. Modelling twist

Picea abies ). Several material parameters were also measured, such as spiral grain angle, shrinkage in all three directions, annual ring width and density. Twist in the studs was measured at four different times at different moisture contents. The amount of twist correlated well with the moisture content and was reversible throughout several moisture changes. When the moisture content decreased, the twist increased and vice versa. About 50% of the variation in twist could be explained by a single parameter, i.e. the average growth ring curvature. All studs with severe twist were cut with its centroid within a radius of 75 mm from the pith. A statistical analysis of the data shows that growth ring curvature and spiral grain angle together explained about 70% of the variation in twist. Other parameters, such as shrinkage strains, density and ring width, did not increase predictability. When using a model developed by Stevens and Johnston (1960), about 66% of the variation in twist could be explained. The model also explained twist quantitatively well. The model included curvature of the growth ring, spiral grain angle and the tangential shrinkage strain.

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Picea abies ). Mehrere Materialeigenschaften wurden ebenfalls gemessen, und zwar: Faserwinkel, Schwinden in drei Richtungen, Jahrringbreite und Dichte. Die Verdrehung der Kanth?lzer wurde zu vier verschiedenen Zeitpunkten bei unterschiedlichen Feuchtegraden gemessen. Das Ausma? der Verdrehung war gut korreliert mit der Feuchte. Mit abnehmender Feuchte stieg die Verdrehung und umgekehrt. Rund 50% der Verdrehungswerte sind durch einen einzigen Parameter erkl?rt, n?mlich die Jahrringkrümmung. Bei allen Kanth?lzern mit starker Verdrehung lag die Mittelachse innerhalb eines Abstandes von 75 mm von der Markr?hre. Die statistische Analyse ergab, da? Jahrringkrümmung und Faserwinkel zusammen ca. 70% der Variation der Verdrehung erkl?ren. Andere Parameter wie Schwindspannungen, Dichte und Jahrringbreite erh?hten die Vorhersagbarkeit nicht. Mit Hilfe des Modells von Stevens und Johnson (1960) konnten rund 66% der Verdrehung erkl?rt werden. Dieses Modell lieferte auch zufriedenstellende quantitative Ergebnisse. Berücksichtigt werden dabei Jahrringkrümmung, Faserwinkel und tangentiale Schwindspannung.

     

Context-free and context-sensitive dynamics in recurrent neural networks

Continuous-valued recurrent neural networks can learn mechanisms for processing context-free languages. The dynamics of such networks is usually based on damped oscillation around fixed points in state space and requires that the dynamical components are arranged in certain ways. It is shown that qualitatively similar dynamics with similar constraints hold for aⁿbⁿcⁿ , a context-sensitive language. The additional difficulty with aⁿbⁿcⁿ , compared with the context-free language aⁿbⁿ , consists of 'counting up' and 'counting down' letters simultaneously. The network solution is to oscillate in two principal dimensions, one for counting up and one for counting down. This study focuses on the dynamics employed by the sequential cascaded network, in contrast to the simple recurrent network, and the use of backpropagation through time. Found solutions generalize well beyond training data, however, learning is not reliable. The contribution of this study lies in demonstrating how the dynamics in recurrent neural networks that process context-free languages can also be employed in processing some context-sensitive languages (traditionally thought of as requiring additional computation resources). This continuity of mechanism between language classes contributes to our understanding of neural networks in modelling language learning and processing.     

A multi-expert system for ranking patents: An approach based on fuzzy pay-off distributions and a TOPSIS–AHP framework

The aim of this paper is to introduce a decision support system that ranks patents based on multiple expert evaluations. The presented approach starts with the creation of three value scenarios for each considered patent by each expert. These are used for the construction of individual fuzzy pay-off distribution functions for the patent value; a consensual fuzzy pay-off distribution is then determined starting from the individual distributions. Possibilistic moments are calculated from the consensus pay-off distribution for each patent and used in ranking them with TOPSIS. It is further showed how the analytic hierarchy process (AHP) can be used to include additional decision variables into the patent selection, thus allowing for a two-tier decision making process. The system is illustrated with a numerical example and the usability of the system and the combination of methods it includes for patent portfolio selection in the real world context is discussed.     

Three-dimensional periodic Voronoi grain models and micromechanical FE-simulations of a two-phase steel

A three-dimensional model is proposed for modeling of microstructures. The model is based on the finite element method with periodic boundary conditions. The Voronoi algorithm is used to generate the geometrical model, which has a periodic grain structure that follows the original boundaries of the Voronoi cells. As an application, the model is used to model a two-phase ferrite/pearlite steel. It is shown that periodic cells with only five grains generate representative stress–strain curves.