Measuring the publishing productivity of economics departments in Europe

Industrial technology grouping is a common phenomenon that occurs as an industry develops and evolves. However, the research on innovation diffusion has given little attention to the role of industrial technology grouping. This paper extends the prior research to analyze the impact of industrial technology grouping on innovation diffusion within the framework of structural embeddedness. In our empirical study, we selected a sample of patents in the smart phone industry during the 2004–2014 period. We used both hierarchical regression analysis and patent citation analysis to explore the impact of industrial technology grouping on innovation diffusion in the two dimensions of clustering and bridging ties, which yielded several valuable results. First, industrial technology grouping is a common phenomenon in the development of industrial technology. Moreover, the dynamic changes of technology clusters are an important driving force shaping the trends and diversity of industrial technology. Second, industrial technology grouping does not have a significant effect on firm innovation diffusion, whereas structural embeddedness directly affects innovation diffusion. Third, industrial technology grouping positively moderates the impact of structural embeddedness on firm innovation diffusion in both dimensions of clustering and bridging ties.     

Diesel fuel based on mixtures of petroleum and vegetable raw materials

Сommercial petroleum diesel, distilled biodiesel and jet fuel JP8 were used to prepare the new fuel blend with physicochemical properties meeting the petroleum diesel standards. The proposed fuel blend consisted of 75% (v/v) petroleum diesel, 20% (v/v) distilled biodiesel and 5% (v/v) jet fuel JP8. The humidity of the prepared fuel blend was regulated using the distilled biodiesel. The key physicochemical properties of fuel such as density, kinematic viscosity, conductivity and water content were measured using standard ASTM methods. The storage stability test for the studied samples showed that they remained unchanged even after 30 and 120 days from the preparation moment. The suggested fuel blend composition may be recommended for the industrial applications due to the benefits of adding 20% of the distilled biodiesel. The composition of the fuel blend meets the European directive which proposes adding up to 20% (v/v) of biodiesel to the petroleum based fuels.     

Increasing airport capacity utilisation through optimum slot scheduling: review of current developments and identification of future needs

Most of the busiest airports worldwide experience serious congestion and delay problems which call for some immediate capacity and demand management action. Solutions aiming to manage congestion through better slot scheduling have lately received a great deal of consideration due to their potential for delivering quick and substantial capacity utilisation improvements. A slot scheduling approach brings promises to cope better with congestion problems in the short to medium run and in a more sustainable way based on existing resources. This paper aims to provide a critical review of current research in declared capacity modelling and strategic slot scheduling. Furthermore, it goes beyond the critical review of current research developments by identifying future research issues and gaps and developing concrete directions towards modelling and solving advanced single airport and network-based slot scheduling problems. Our research findings suggest that the next generation of slot scheduling models should explore variations of currently used objectives (e.g., alternative expressions of schedule delay) and most importantly enrich them with fairness and equity, resource utilisation and environmental considerations. Future modelling efforts should also aim to further investigate airlines’ utility of alternative slot allocation outcomes, including various acceptability measures and levels of tolerance against schedule displacements. Last but not least, future research should intensively focus on the development and validation of computationally viable and robust slot scheduling models being able to capture the complexity, dynamic nature and weather-induced uncertainty of airport operations, along with hybrid solution approaches being able to deal with the size and complexity of slot allocation at network level.     

Risk attitude reversals in drivers' route choice when range of travel time information is provided

Automobile drivers were recently found to be risk averse when choosing among routes that had an average travel time shorter than the certain travel time of a route considered as a reference. Conversely, drivers were found to be risk seeking when choosing among routes that had an average travel time longer than the certain travel time of the reference route. In a driving simulation study in which the reference route had a range of travel times, this pattern was replicated when thereference range was smaller than the ranges of the available routes. However, the pattern was reversed when the reference range was larger than the ranges of the available routes. We recently proposed a simple heuristic model that fit the relatively complex data quite well. Actual or potential applications of this research include the design of variable message signs and of route choice support systems.     

Research output evaluation of two University Departments in Greece with the use of bibliometric indicators

The results of a study for evaluating research performance of two Greek University Departments of Mathematics are presented. In order to achieve this elements from the Sussex and Leiden methodologies of constructing and using bibliometric indicators were used. Comparison of the two groups were based on their similarities. The convergence of bibliometric indicators procedure as applied in Leiden methodology together with a number new bibliometric indicators were used. Results shown that bibliometric indicators if applied properly may give very interesting information on the research performance and nature of research carried out in University Departments.     

Synthesis of blue luminescent si nanoparticles using atmospheric-pressure microdischarges

Silicon nanoparticles are synthesized from a mixture of argon/silane in a continuous flow atmospheric-pressure microdischarge reactor. Particles nucleate and grow to a few nanometers (1-3 nm) in diameter before their growth is abruptly terminated in the short residence time microreactor. Narrow size distributions are obtained as inferred from size classification and imaging. As-grown Si nanoparticles collected in solution exhibit room-temperature photoluminescence that peaks at 420 nm with a quantum efficiency of 30%; the emission is stable for months in ambient air.     

A monolithic silicon optoelectronic transducer as a real-time affinity biosensor

An optical real-time affinity biosensor, which is based on a monolithic silicon optoelectronic transducer and a microfluidic module, is described. The transducer monolithically integrates silicon avalanche diodes as light sources, silicon nitride optical fibers, and p/n junction detectors and efficiently intercouples these elements through a self-alignment technique. The transducer surface is hydrophilized by oxygen plasma treatment, silanized with (3-aminopropyl)triethoxysilane and bioactivated through adsorption of the biomolecular probes. The use of a microfluidic module allows real-time monitoring of the binding reaction of the gold nanoparticle-labeled analytes with the immobilized probes. Their binding within the evanescent field at the surface of the optical fiber causes attenuated total reflection of the waveguided modes and reduction of the detector photocurrent. The biotin-streptavidin model assay was used for the evaluation of the analytical potentials of the device developed. Detection limits of 3.8 and 13 pM in terms of gold nanoparticle-labeled streptavidin were achieved for continuous- and stopped-flow assay modes, respectively. The detection sensitivity was improved by silver plating of the immobilized gold nanoparticles, and a detection limit of 20 fM was obtained after 20-min of silver plating. In addition, two different analytes, streptavidin and anti-mouse IgG, were simultaneously assayed on the same chip demonstrating the multianalyte potential of the sensor developed.     

Ultra Low Power CORDIC Processor for Wireless Communication Algorithms

We designed and implemented an ultra low power CORDIC processor which targets the implementation of advanced wireless communications algorithms based on Givens rotations and Householder reflections. We propose a modified CORDIC algorithm and architecture, and we elaborate on the low power architectural and algorithmic techniques for minimizing its power consumption. Our CORDIC implementation consumes, in rotate mode, on average 50 W @ 10 MHz under 1 V supply voltage in a .25 m technology.     

Use of artificial neural networks for the accurate prediction of peptide liquid chromatography elution times in proteome analyses

The use of artificial neural networks (ANNs) is described for predicting the reversed-phase liquid chromatography retention times of peptides enzymatically digested from proteome-wide proteins. To enable the accurate comparison of the numerous LC/MS data sets, a genetic algorithm was developed to normalize the peptide retention data into a range (from 0 to 1), improving the peptide elution time reproducibility to approximately 1%. The network developed in this study was based on amino acid residue composition and consists of 20 input nodes, 2 hidden nodes, and 1 output node. A data set of approximately 7000 confidently identified peptides from the microorganism Deinococcus radiodurans was used for the training of the ANN. The ANN was then used to predict the elution times for another set of 5200 peptides tentatively identified by MS/MS from a different microorganism (Shewanella oneidensis). The model was found to predict the elution times of peptides with up to 54 amino acid residues (the longest peptide identified after tryptic digestion of S. oneidensis) with an average accuracy of approximately 3%. This predictive capability was then used to distinguish with high confidence isobar peptides otherwise indistinguishable by accurate mass measurements as well as to uncover peptide misidentifications. Thus, integration of ANN peptide elution time prediction in the proteomic research will increase both the number of protein identifications and their confidence.     

Investigation of carbon incorporation in znse: Effects on morphology,electrical, and photoluminescence properties

Observations of carbon incorporation in epitaxial ZnSe films grown by metalorganic chemical vapor deposition are presented. Carbon is detected by secondary ion mass spectroscopy (SIMS) measurements in all ZnSe films grown from methylallylselenide and dimethylzinc. The presence of carbon in the films is correlated with a new bound excitonic emission appearing at 2.7920 eV which dominates the near-band-edge low-temperature photoluminescence spectra of all carbon contaminated films. This peak is also observed when growth is commenced from diethylselenide, under certain growth conditions, but not from hydrogen selenide. The effect of the carbon contamination is discussed in terms of variations in surface morphology, electrical and luminescence properties of as-grown films. Control of the carbon concentration is demonstrated by alternating between hydrogen selenide and methylallylselenide during growth. Strategies to avoid carbon contamination in ZnSe are also proposed. Author to whom correspondence should be addressed