The effect of grain size on the mechanical properties of AM-SC1

Australian Magnesium Corporation, in collaboration with the Cooperative Research Centre for Cast Metals Manufacturing (CAST) and Magnesium Elektron Limited, has developed a magnesium alloy, AM-SC1, which has been specifically designed for engine block applications [1]. This alloy has been used for the engine block of the Genois LE turbo charged diesel injection motor developed by AVL List [2].

Viscoelasticity and high buckling stress of dense carbon nanotube brushes

We report on the mechanical behavior of a dense brush of small-diameter (1–3 nm) non-catalytic multiwall (2–4 walls) carbon nanotubes (CNTs), with ~10 times higher density than CNT brushes produced by other methods. Under compression with spherical indenters of different radii, these highly dense CNT brushes exhibit a higher modulus (~17–20 GPa) and orders of magnitude higher resistance to buckling than vapor phase deposited CNT brushes or carbon walls. We also demonstrate the viscoelastic behavior, caused by the increased influence of the van der Waals’ forces in these highly dense CNT brushes, showing their promise for energy-absorbing coatings.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.

The integration of ProxiMAX randomisation with CIS display for the high-throughput production of novel peptides

Saturation mutagenesis is a powerful tool in modern protein engineering. This can allow the analysis of potential new properties thus allowing key residues within a protein to be targeted and randomised. However, the creation of large libraries using conventional saturation mutagenesis with degenerate codons (NNN or NNK) has inherent redundancy and disparities in residue representation. In this we describe the combination of ProxiMAX randomisation and CIS display for the use of generating novel peptides. Unlike other methods ProxiMAX randomisation does not require any intricate chemistry but simply utilises synthetic DNA and molecular biology techniques. Designed ‘MAX’ oligonucleotides were ligated, amplified and digested in an iterative cycle. Results show that randomised ‘MAX’ codons can be added sequentially to the base sequence creating a series of randomised non-degenerate codons that can subsequently be inserted into a gene. CIS display (Isogencia, UK) is an in vitro DNA based screening method that creates a genotype to phenotype link between a peptide and the nucleic acid that encodes it. The use of straight forward in vitro transcription/translation and other molecular biology techniques permits ease of use along with flexibility making it a potent screening technique. Using ProxiMAX randomisation in combination with CIS display, the aim is to produce randomised anti-nerve growth factor (NGF) and calcitonin gene-related (CGRP) peptides to demonstrate the high-throughput nature of this combination.