Economic prosperity, suburbanization, and the creative workforce : findings from Australian suburban communities

This paper considers the changing relationship between economic prosperity and Australian suburbs, noting that what has been termed “the first suburban nation” in experiencing an intensification of suburban growth in the 2000s, in the context of economic globalization. The paper reports on a three-year Australian Research Council funded project into “Creative Suburbia”, identifying the significant percentage of the creative industries workforce who live in suburban areas. Drawing on case studies from suburbs in the Australian cities of Brisbane and Melbourne, it notes the contrasts between the experience of these workers, who are generally positive towards suburban life, and the underlying assumptions of “creative cities” policy discourse that such workers prefer to be concentrated in high density inner urban creative clusters.

Media as creative industries : conglomeration and globalization as accumulation strategies in an age of digital media

This chapter will begin by considering some of the distinctive features of media as creative industries, including their assessment of risk and return on investment, team-based production, the management of creativity, the value chain of production, distribution and circulation, and the significance of intellectual property in their revenue strategies. It will then critically appraise three strategies to capture new markets and revenue streams in the context of the rise of the Internet, digital media and globally networked distribution. The three strategies to be considered are conglomeration, networking and globalization, and the focus will be on the media giants such as News Corporation, Disney and Time-Warner. It will be argued that all three present considerable challenges in their application, and digital media technologies are weakening rather than strengthening their capacity to control the global media environment. The chapter will conclude with consideration of some implications of this analysis for questions of media power.

Cloning and characterization of a novel human gene related to vascular endothelial growth factor

This paper describes the cloning and characterization of a new member of the vascular endothelial growth factor (VEGF) gene family, which we have designated VRF for VEGF-related-factor. Sequencing of cDNAs from a human fetal brain library and RT-PCR products from normal and tumor tissue cDNA pools indicate two alternatively spliced messages with open reading frames of 621 and 564 bp, respectively. The predicted proteins differ at their carboxyl ends resulting from a shift in the open reading frame. Both isoforms show strong homology to VEGF at their amino termini, but only the shorter isoform maintains homology to VEGF at its carboxyl terminus and conserves all 16 cysteine residues of VEGF165. Similarity comparisons of this isoform revealed overall protein identity of 48% and conservative substitution of 69% with VEGF189. VRF is predicted to contain a signal peptide, suggesting that it may be a secreted factor. The VRF gene maps to the D11S750 locus at chromosome band 11q13, and the protein coding region, spanning approximately 5 kb, is comprised of 8 exons that range in size from 36 to 431 bp. Exons 6 and 7 are contiguous and the two isoforms of VRF arise through alternate splicing of exon 6. VRF appears to be ubiquitously expressed as two transcripts of 2.0 and 5.5 kb; the level of expression is similar among normal and malignant tissues.

Targeting mutant fibroblast growth factor receptors in cancer

Fibroblast growth factor receptors (FGFRs) play diverse roles in the control of cell proliferation, cell differentiation, angiogenesis and development. Activating the mutations of FGFRs in the germline has long been known to cause a variety of skeletal developmental disorders, but it is only recently that a similar spectrum of somatic FGFR mutations has been associated with human cancers. Many of these somatic mutations are gain-of-function and oncogenic and create dependencies in tumor cell lines harboring such mutations. A combination of knockdown studies and pharmaceutical inhibition in preclinical models has further substantiated genomically altered FGFR as a therapeutic target in cancer, and the oncology community is responding with clinical trials evaluating multikinase inhibitors with anti-FGFR activity and a new generation of specific pan-FGFR inhibitors.

Vertical growth and resonator properties of hexagonally shaped zinc oxide nanonails

We synthesized vertically aligned nail-shaped ZnO nanocrystal arrays on silicon substrates via a combination of a carbothermal reduction method and textured ZnO seeding layers that were precoated on silicon substrates by thermally decomposing zinc acetate, and studied their optical properties using cathodoluminescence (CL) and photoluminescence techniques. The ZnO nanonails show a sharp band-gap edge UV emission and a defect-related broad green emission. Monochromatic CL images of an individual ZnO nanonail show variations in spatial distributions of respective CL bands that had different origins. We attribute the spatial variation of CL images to an uneven distribution of luminescent defects and/or a structure-related light out-coupling from hexagonal ZnO nanostructures. The most distinct CL feature from the hexagonal head of an individual ZnO nanonail was the occurrence of a series of distinct resonant peaks within the visible wavelength range. It appeared that the head of a nanonail played the role of a hexagonal cavity so that polarizationdependent whispering gallery modes were stimulated by electron beam excitation.

Catalyst-free growth and optical properties of vertically aligned ZnO Nanorod Arrays on Si substrates covered with thin buffer layers

Vertically aligned ZnO nanorods have been grown on silicon substrates pre-coated with thin, less than 10 nm, textured ZnO seeding layers via a vapor-solid mechanism. The ZnO seeding layers, which were essential for vertical alignment of ZnO nanorods without using any metal catalyst, were prepared by decomposing zinc acetate. The structure and the luminescence properties of the ZnO nanorods synthesized onto ZnO seeding layers were investigated and their morphologies were compared with those of single-crystalline GaN substrates and silicon substrates covered with sputtered ZnO flms. Patterning of ZnO seed layers using photolithography allowed the fabrication of patterned ZnO-nanorod arrays.

Cross likelihood ratio based speaker clustering using eigenvoice models

This paper proposes the use of eigenvoice modeling techniques with the Cross Likelihood Ratio (CLR) as a criterion for speaker clustering within a speaker diarization system. The CLR has previously been shown to be a robust decision criterion for speaker clustering using Gaussian Mixture Models. Recently, eigenvoice modeling techniques have become increasingly popular, due to its ability to adequately represent a speaker based on sparse training data, as well as an improved capture of differences in speaker characteristics. This paper hence proposes that it would be beneficial to capitalize on the advantages of eigenvoice modeling in a CLR framework. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 35.1% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Manufacturing Yield Improvement by Clustering

Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.

Hyaluronic acid : evaluation as a potential delivery vehicle for vitronectin:growth factor complexes in wound healing applications

We have previously reported that novel vitronectin:growth factor (VN:GF) complexes significantly increase re-epithelialization in a porcine deep dermal partial-thickness burn model. However, the potential exists to further enhance the healing response through combination with an appropriate delivery vehicle which facilitates sustained local release and reduced doses of VN:GF complexes. Hyaluronic acid (HA), an abundant constituent of the interstitium, is known to function as a reservoir for growth factors and other bioactive species. The physicochemical properties of HA confer it with an ability to sustain elevated pericellular concentrations of these species. This has been proposed to arise via HA prolonging interactions of the bioactive species with cell surface receptors and/or protecting them from degradation. In view of this, the potential of HA to facilitate the topical delivery of VN:GF complexes was evaluated. Two-dimensional (2D) monolayer cell cultures and 3D de-epidermised dermis (DED) human skin equivalent (HSE) models were used to test skin cell responses to HA and VN:GF complexes. Our 2D studies revealed that VN:GF complexes and HA stimulate the proliferation of human fibroblasts but not keratinocytes. Experiments in our 3D DED-HSE models showed that VN:GF complexes, both alone and in conjunction with HA, led to enhanced development of both the proliferative and differentiating layers in the DED-HSE models. However, there was no significant difference between the thicknesses of the epidermis treated with VN:GF complexes alone and VN:GF complexes together with HA. While the addition of HA did not enhance all the cellular responses to VN:GF complexes examined, it was not inhibitory, and may confer other advantages related to enhanced absorption and transport that could be beneficial in delivery of the VN:GF complexes to wounds.

Relationship to the bereaved and perceptions of severity of trauma differentiate elements of posttraumatic growth

The field of bereavement and grief has been expanding to recognise the potential for growth following the loss of a loved one. This study sought to examine the effect of the relationship to the deceased and perceptions of the severity of the trauma on dimensions of posttraumatic growth. Participants were 146 people who had lost either: a) a first degree relative, b) a second degree relative, or c) a non-related friend. Results demonstrated that both severity and the relationship to the bereaved differentiate posttraumatic growth outcomes. For example, participants who had lost a first degree relative reported higher levels of growth than those who had lost a second degree relative. Consistent with previous research in general trauma populations, the more severe the loss was rated, the higher the levels of growth. Implications for practice are discussed.

Factors effecting motor vehicle growth in Dhaka

Dhaka’s traffic is heterogeneous, both motorized (MT) and non-motorized (NMT) transport are common. Traffic congestion has become a part of city dwellers’ lives. This paper explores the factors for motor vehicle growth in Dhaka. The scope of the paper will be limited to literature review...

Identifying differences in safe roads and crash prone roads using clustering data mining

Road asset managers are overwhelmed with a high volume of raw data which they need to process and utilise in supporting their decision making. This paper presents a method that processes road-crash data of a whole road network and exposes hidden value inherent in the data by deploying the clustering data mining method. The goal of the method is to partition the road network into a set of groups (classes) based on common data and characterise the class crash types to produce a crash profiles for each cluster. By comparing similar road classes with differing crash types and rates, insight can be gained into these differences that are caused by the particular characteristics of their roads. These differences can be used as evidence in knowledge development and decision support.