Substrate Specificity of the Highly Thermostable Esterase EstDZ3

Esterases are among the most studied enzymes, and their applications expand into several branches of industrial biotechnology. Yet, despite the fact that information on their substrate specificity is crucial for selecting or designing the best fitted biocatalyst for the desired application, it cannot be predicted from their amino acid sequence. In this work, we studied the substrate scope of the newly discovered hydrolytic extremozyme, EstDZ3, against a library of esters with variable carbon chain lengths in an effort to understand the crucial amino acids for the substrate selectivity of this enzyme. EstDZ3 appears to be active against a wide range of esters with high selectivity towards medium- to long-carbon chain vinyl esters. In-silico studies of its 3D structure revealed that the selectivity might arise from the mainly hydrophobic nature of the active site's environment.     

Carbon nanotube-based polymer composites: A trade-off between manufacturing cost and mechanical performance

A methodology was devised to evaluate the newly-developed carbon nanotube reinforced polymer composites by means of mechanical performance and manufacturing cost. Glass fibre reinforced-epoxy composite plates were produced having different parameters: (a) three manufacturing processes, (b) geometrical dimensions, (c) carbon nanotubes concentration in the epoxy resin and finally (d) modified resin infusion temperature. Tensile coupons were machined out of the manufactured plates and their quasi-static mechanical properties were evaluated. Three cost models were developed to assess plates and tensile coupons manufacturing cost for each different case. Optimal values were evaluated for major manufacturing parameters, driving force being the mechanical properties of interest (quality) as well as their low manufacturing cost. It is demonstrated that the added cost to manufacture such nano-reinforced composites is attributed to increase strength on the expense of ductility; the main benefit of the carbon nanotube-based polymer composites seems to be their ability to be monitored. Almost 20% added cost is paid to attain this new function of piezo-resistivity for the RTM process, while this amount further increases for the non-automated processes such as the Hand Lay-up.     

Autonomous Vehicle Emergency Recovery Tool: A Cooperative Robotic System for Car Extraction

Vehicles have been proven to be an ideal means for terrorists because they can be meticulously prepared well in advance before being deployed in urban and public places. To increase the risk and burden of explosive ordnance disposal teams, third‐party vehicles have also been used to block the access path to the explosive loaded vehicle. In this paper, we present a multirobot system that can remove vehicles from confined spaces with delicate handling, swiftly and in any direction to a safer disposal point. The new lifting robots, capable of omnidirectional movement, autonomously underride the identified vehicle and dock to its wheels for a synchronized lifting and extraction. The validity and efficiency of the novel robotic system is illustrated via experiments in an indoor parking lot, demonstrating successful autonomous navigation, docking, lifting, and extraction of a conventional car for a total covered distance of 20 m.     

Function-integrative Lightweight Engineering – Design Methods and Applications

Function-integrative lightweight engineering represents an essential element in modern design methods. Currently, there is a great need for the incorporation of sensors, actuators and electronics in novel, demand-oriented components. In contrast to a subsequent, mostly adhesive bonding, structural integration offers numerous advantages, for example in terms of space requirements and robustness. This paper demonstrates the potential of integrated sensors for various industrial sectors based on selected examples from mechanical engineering, aviation, mobility, sports, and medical technology.     

Artificial neural network models for the prediction of surface roughness in electrical discharge machining

In the present paper Artificial Neural Networks (ANNs) models are proposed for the prediction of surface roughness in Electrical Discharge Machining (EDM). For this purpose two well-known programs, namely Matlab^® with associated toolboxes, as well as Netlab^®, were emplo- yed. Training of the models was performed with data from an extensive series of EDM experiments on steel grades; the proposed models use the pulse current, the pulse duration, and the processed material as input parameters. The reported results indicate that the proposed ANNs models can satisfactorily predict the surface roughness in EDM. Moreover, they can be considered as valuable tools for the process planning for EDMachining.     

The effect of Fe on the catalytic behavior of model Pd-Rh/CeO2-Al2O3 three-way catalyst

The present work attempts to address the issue whether iron (Fe) which is accumulated on the surface of “three-way” catalysts (TWCs) used in gasoline-driven cars is a true chemical poison of their catalytic activity. This important issue from a scientific and technological point of view is addressed via catalytic activity, temperature-programmed surface reaction (TPSR), and X-ray photoelectron spectroscopy (XPS) measurements over a model TWC (1 wt% Pd–Rh/20 wt% CeO₂–Al₂O₃). It was found that deposition of Fe up to the level of 0.4 wt% (an average concentration found in aged commercial TWCs) on the model TWC does not deteriorate its activity towards CO and C₃H₆ oxidation, and reduction of NO by H₂. Instead it was found that iron improves significantly the T₅₀ parameter in the activity versus temperature profile. Small Fe clusters in contact with the noble metal (Pd and Rh) particles due to the lower work function of Fe compared to Pd and Rh act likely as a source of electron flow towards the noble metals (as evidenced by XPS measurements), thus altering their surface work function and adsorption energetics of reaction intermediates. The latter have increased significantly the activity of the model TWC towards oxidation of CO and propylene, and to a lesser extent the activity towards the reduction of NO by H₂. The presence of Fe on the surface of the model TWC provided and/or created also new active catalytic sites for the reactions investigated. According to previous work from this laboratory, iron up to the level of 0.4 wt% was shown not to deteriorate the oxygen storage capacity (OSC) of the same model TWC used in the present work. Thus, it could be concluded that Fe when deposited on a commercial TWC at least up to the level of 0.4 wt% acts likely as a promoter than a poison of its catalytic activity.     

Network coding-based cooperative ARQ scheme for VANETs

In this paper we introduce a novel Network Coding-based Medium Access Control (MAC) protocol for Vehicular Ad Hoc Networks (VANETs) that use cooperative Automatic Repeat reQuest (ARQ) techniques. Our protocol coordinates the channel access among a set of relays capable of using network coding in order to minimize the number of the total transmissions, thus enhancing the performance of the network in terms of Quality of Service (QoS) metrics. The proposed solution is compared to other cooperative schemes, while analytical and simulation results are provided to evaluate our protocol.     

The remarkable effect of oxygen on the N2 selectivity of water catalytic denitrification by hydrogen

The selective catalytic reduction of nitrates (NO3-) in pure water toward N2 formation by the use of gaseous H2 and in the presence of O2 (air) at 1 atm total pressure and 25 degrees C has been investigated over Pd-Cu supported on various mixed metal oxides, x wt % MO(x(/gamma-Al2O3 (MO(x) = CeO2, SrO, Mn2O3, Cr2O3, Y2O3, and TiO2). It is demonstrated for the firsttime that a remarkable improvement in N2 reaction selectivity (by 80 percentage units) can be achieved when oxygen is present in the reducing feed gas stream. In particular, significantly lower reaction selectivities toward NH4+ and NO2- can be obtained, whereas the rate of NO3- conversion is not significantly affected. Moreover, it was shown thatthe same effect is obtained over the Pd-Cu-supported catalysts irrespective to the chemical composition of support and the initial concentration of nitrates in water used. The Pd-Cu clusters supported on 4.8 wt%TiO2/gamma-Al2O3 resulted in a solid with the best catalytic behavior compared with the rest of supports examined, both in the presence and in the absence of oxygen in the reducing feed gas stream. DRIFTS studies performed following catalytic reduction by H2 of NO3- in water revealed that the presence of TiO2 in the Pd-Cu/TiO2-Al2O3 system enhanced the reactivity of adsorbed bidentate nitrate species toward H2. Nitrosyl species adsorbed on the alumina and titania support surfaces are considered as active intermediate species of the selective catalytic reduction of NO3- by H2 in water. Pd-Cu/TiO2-Al2O3 appears to be the most selective catalyst ever reported in the literature for the reduction of nitrates present in pure water into N2 by a reducing gas mixture of H2/air.