Globalisation, transnational academic mobility and the Chinese knowledge diaspora: an Australian case study

The master discourses of economic globalisation and the knowledge economy each cite knowledge diasporas as vital ‘trans-national human capital’. Based on a case study of a major Australian university, this article examines the potential to deploy China's large and highly-skilled diaspora in the service of Chinese and Australian scientific and technological development. It finds that at a time when much of the world is deeply mired in a global financial crisis, this treasured resource of highly-skilled intellectuals assumes even greater significance. Meanwhile, there are key challenges to be confronted to fully utilise China's overseas talent. It argues that the Chinese knowledge diaspora are a modern kind of cosmopolitan literati, and could contribute actively to higher education internationalisation in both Australia and China.postprin

Lagrangian and Eulerian dataset of the wake downstream of a smooth cylinder at a Reynolds number equal to 3900.

The dataset contains Eulerian velocity and pressure fields, and Lagrangian particle trajectories of the wake flow downstream of a smooth cylinder at a Reynolds number equal to 3900. An open source Direct Numerical Simulation (DNS) flow solver named Incompact3d was used to calculate the Eulerian field around the cylinder. The synthetic Lagrangian tracer particles were transported using a fourth-order Runge-Kutta scheme in time and trilinear interpolations in space. Trajectories of roughly 200,000 particles for two 3D sub-domains are available to the public. This dataset can be used as a test case for tracking algorithm assessment, exploring the Lagrangian physics, statistic analyses, machine learning, and data assimilation interests

Effect of graphite on copper bioleaching fromwaste printed circuit boards

The efficient extraction of copper as a valuable metal from waste printed circuit boards (WPCBs) is currently attracting growing interest. Here, we systematically investigated the impact of bacteria on the efficiency of copper leaching from WPCBs, and evaluated the effect of graphite on bioleaching performance. The HQ0211 bacteria culture containing Acidithiobacillus ferrooxidans, Ferroplasma acidiphilum, and Leptospirillum ferriphilum enhanced Cu-leaching performance in either ferric sulfate and sulfuric acid leaching, so a final leaching of up to 76.2% was recorded after 5 days. With the addition of graphite, the percentage of copper leaching could be increased to 80.5%. Single-factor experiments confirmed the compatibility of graphite with the HQ0211 culture, and identified the optimal pulp density of WPCBs, the initial pH, and the graphite content to be 2% (w/v), 1.6, and 2.5 g/L, respectively.</jats:p

Classification of Ultrasonic Weld Inspection Data Using Principal Component Analysis

Recent inservice inspection experience, round robin tests of ultrasonic inspection reliability [1] and calculations of flaw detection reliability necessary for specific nuclear power plant applications have consistently shown the need to improve the reliability of ultrasonic inspection. The need to improve ultrasonic inspection reliability is further emphasized when one reviews the pass rates for performance demonstrations specified by ASME Section XI Appendix VIII

The 'At-risk mental state' for psychosis in adolescents : clinical presentation, transition and remission.

Despite increased efforts over the last decade to prospectively identify individuals at ultra-high risk of developing a psychotic illness, limited attention has been specifically directed towards adolescent populations (<18 years). In order to evaluate how those under 18 fulfilling the operationalised criteria for an At-Risk Mental State (ARMS) present and fare over time, we conducted an observational study. Participants (N = 30) generally reported a high degree of functional disability and frequent and distressing perceptual disturbance, mainly in the form of auditory hallucinations. Seventy percent (21/30) were found to fulfil the criteria for a co-morbid ICD-10 listed mental health disorder, with mood (affective; 13/30) disorders being most prevalent. Overall transition rates to psychosis were low at 24 months follow-up (2/28; 7.1 %) whilst many participants demonstrated a significant reduction in psychotic-like symptoms. The generalisation of these findings may be limited due to the small sample size and require replication in a larger sample

Proteomics Analysis of Ovarian Cancer Cell Lines and Tissues Reveals Drug Resistance-associated Proteins

Background: Carboplatin and paclitaxel form the cornerstone of chemotherapy for epithelial ovarian cancer, however, drug resistance to these agents continues to present challenges. Despite extensive research, the mechanisms underlying this resistance remain unclear. Materials and Methods: A 2D-gel proteomics method was used to analyze protein expression levels of three human ovarian cancer cell lines and five biopsy samples. Representative proteins identified were validated via western immunoblotting. Ingenuity pathway analysis revealed metabolomic pathway changes. Results: A total of 189 proteins were identified with restricted criteria. Combined treatment targeting the proteasome-ubiquitin pathway resulted in re-sensitisation of drug-resistant cells. In addition, examination of five surgical biopsies of ovarian tissues revealed α-enolase (ENOA), elongation factor Tu, mitochondrial (EFTU), glyceraldehyde-3-phosphate dehydrogenase (G3P), stress-70 protein, mitochondrial (GRP75), apolipoprotein A-1 (APOA1), peroxiredoxin (PRDX2) and annexin A (ANXA) as candidate biomarkers of drug-resistant disease. Conclusion: Proteomics combined with pathway analysis provided information for an effective combined treatment approach overcoming drug resistance. Analysis of cell lines and tissues revealed potential prognostic biomarkers for ovarian cancer

Cloud computing—effect of evolutionary algorithm on load balancing

© Springer International Publishing Switzerland 2015 In cloud computing due to the multi-tenancy of the resources, there is an essential need for effective load management to ensure an efficient load sharing. Depends on the structure of the tasks, different algorithms could be applied to distribute the load. Workflow scheduling as one of those load distribution algorithms, is specifically designed to schedule the dependent tasks on available resources. Considering a job as an elastic network of dependent tasks, this paper describes how evolutionary algorithm, with its mathematical apparatus, could be applied as workflow scheduling in cloud computing. In this research, the impact of Generalized Spring Tensor Model on workflow load balancing, in context of mathematical patterns have been studied. This research can establish patterns in cloud computing which can be applied in designing the heuristic workflow load balancing algorithms to identify the load patterns of the cloud network. Furthermore, the outcome of this research can help the end users to recognize the threats of tasks failure in processing the e-business and e-since data in cloud environment

Selective Constraints on Amino Acids Estimated by a Mechanistic Codon Substitution Model with Multiple Nucleotide Changes

Empirical substitution matrices represent the average tendencies of substitutions over various protein families by sacrificing gene-level resolution. We develop a codon-based model, in which mutational tendencies of codon, a genetic code, and the strength of selective constraints against amino acid replacements can be tailored to a given gene. First, selective constraints averaged over proteins are estimated by maximizing the likelihood of each 1-PAM matrix of empirical amino acid (JTT, WAG, and LG) and codon (KHG) substitution matrices. Then, selective constraints specific to given proteins are approximated as a linear function of those estimated from the empirical substitution matrices. Akaike information criterion (AIC) values indicate that a model allowing multiple nucleotide changes fits the empirical substitution matrices significantly better. Also, the ML estimates of transition-transversion bias obtained from these empirical matrices are not so large as previously estimated. The selective constraints are characteristic of proteins rather than species. However, their relative strengths among amino acid pairs can be approximated not to depend very much on protein families but amino acid pairs, because the present model, in which selective constraints are approximated to be a linear function of those estimated from the JTT/WAG/LG/KHG matrices, can provide a good fit to other empirical substitution matrices including cpREV for chloroplast proteins and mtREV for vertebrate mitochondrial proteins. The present codon-based model with the ML estimates of selective constraints and with adjustable mutation rates of nucleotide would be useful as a simple substitution model in ML and Bayesian inferences of molecular phylogenetic trees, and enables us to obtain biologically meaningful information at both nucleotide and amino acid levels from codon and protein sequences.Comment: Table 9 in this article includes corrections for errata in the Table 9 published in 10.1371/journal.pone.0017244. Supporting information is attached at the end of the article, and a computer-readable dataset of the ML estimates of selective constraints is available from 10.1371/journal.pone.001724

Doppler velocimetry of spin propagation in a two-dimensional electron gas

Controlling the flow of electrons by manipulation of their spin is a key to the development of spin-based electronics. While recent demonstrations of electrical-gate control in spin-transistor configurations show great promise, operation at room temperature remains elusive. Further progress requires a deeper understanding of the propagation of spin polarization, particularly in the high mobility semiconductors used for devices. Here we report the application of Doppler velocimetry to resolve the motion of spin-polarized electrons in GaAs quantum wells driven by a drifting Fermi sea. We find that the spin mobility tracks the high electron mobility precisely as a function of T. However, we also observe that the coherent precession of spins driven by spin-orbit interaction, which is essential for the operation of a broad class of spin logic devices, breaks down at temperatures above 150 K for reasons that are not understood theoretically