Effect of moisture and filler content on the structural,thermal and dielectric properties of polyamide‐6/boehmite alumina nanocomposites

Polyamide‐6 (PA‐6)/boehmite alumina (BA) nanocomposites were prepared via direct melt compounding. Structural, thermal and dielectric properties of ‘as‐received’ (including moisture) and ‘dried’ (thermally treated) specimens were examined. The BA nanofiller was homogeneously dispersed in the PA‐6 matrix. XRD and FTIR revealed that crystallization of PA‐6 in the γ phase was favoured over α phase with increasing BA content. The crystallinity index (CI) and the percentage of α and γ phases were also evaluated. Dried specimens exhibited a lower CI than as‐received specimens while the CI decreased with the addition of filler. Broadband dielectric spectroscopy revealed the presence of γ, β and α relaxations, the Maxwell–Wagner–Sillars effect and the contribution of conductivity relaxation in the as‐received samples. The drying procedure unmasked a double feature of both β and α modes. The results of the complementary techniques were analysed and the effects of moisture and/or the incorporation of BA nanofiller on the microstructure of the PA‐6 matrix are disclosed. © 2019 Society of Chemical Industry     

Semantic content of motorcycle riders’ eye fixations during lane-splitting

A naturalistic field observation study is presented, exploring the experienced riders’ eye fixations on specific traffic objects and their relative s     

Bibliometric analysis of the evolution of biochar research trends and scientific production

Clean Technologies and Environmental Policy - Biochar has caught great attention over the last decade, yielding a large number of publications in a broad range of disciplines. This scientometric...     

Development of surrogate models for the prediction of the flow around an aircraft propeller

In the present work, the derivation of two surrogate models (SMs) for modelling the flow around a propeller for small aircrafts is presented. Both methodologies use derived functions based on computations with the detailed propeller geometry. The computations were performed using k–ω shear stress transport for modelling turbulence. In the SMs, the modelling of the propeller was performed in a computational domain of disk-like geometry, where source terms were introduced in the momentum equations. In the first SM, the source terms were polynomial functions of swirl and thrust, mainly related to the propeller radius. In the second SM, regression analysis was used to correlate the source terms with the velocity distribution through the propeller. The proposed SMs achieved faster convergence, in relation to the detail model, by providing also results closer to the available operational data. The regression-based model was the most accurate and required less computational time for convergence.     

The relationship between output and unemployment: Evidence from Greek regions

This research note investigates the relationship between output and unemployment in Greece at a regional level through the implementation of Okunss law. Current practice is primarily restricted to the national level, and thus ignores the regional dimension of this relationship. To this end, we apply modern unit root test and cointegration techniques based on panel data settings. Using panel data is necessary because typical spans of economic time series are short, so the entire panel must be exploited in order to draw sharper inferences. The empirical results reveal that Okuns law can be confirmed for six out of the 13 regions we examine.Received: 20 November 2002, Accepted: 5 November 2003, JEL Classification: C23, E32, O18Dimitris K. Christopoulos: I would like to thank two anonymous referees and the European editor, whose comments greatly strengthened the notes content. Thanks are also extended to Dr. V. Arapoglou for helpful suggestions on an earlier version. The usual disclaimer applies     

A GENERALIZED BLOCK BOOTSTRAP FOR SEASONAL TIME SERIES

When time‐series data contain a periodic/seasonal component, the usual block bootstrap procedures are not directly applicable. We propose a modification of the block bootstrap – the generalized seasonal block bootstrap (GSBB) – and show its asymptotic consistency without undue restrictions on the relative size of the period and block size. Notably, it is exactly such restrictions that limit the applicability of other proposals of block bootstrap methods for time series with periodicities. The finite‐sample performance of the GSBB is also illustrated by means of a small simulation experiment.