Real, complex, and binary semantic vectors

This paper presents a combined structure for using real, complex, and binary valued vectors for semantic representation. The theory, implementation, and application of this structure are all significant. For the theory underlying quantum interaction, it is important to develop a core set of mathematical operators that describe systems of information, just as core mathematical operators in quantum mechanics are used to describe the behavior of physical systems. The system described in this paper enables us to compare more traditional quantum mechanical models (which use complex state vectors), alongside more generalized quantum models that use real and binary vectors. The implementation of such a system presents fundamental computational challenges. For large and sometimes sparse datasets, the demands on time and space are different for real, complex, and binary vectors. To accommodate these demands, the Semantic Vectors package has been carefully adapted and can now switch between different number types comparatively seamlessly. This paper describes the key abstract operations in our semantic vector models, and describes the implementations for real, complex, and binary vectors. We also discuss some of the key questions that arise in the field of quantum interaction and informatics, explaining how the wide availability of modelling options for different number fields will help to investigate some of these questions.

Orthopaedics and Trauma Queensland Annual Report 2011

Orthopaedics and Trauma Queensland, a Centre for Research and Education in Musculoskeletal Disorders, is an internationally recognised research group that is developing into an international leader in research and education. It provides a stimulus for research, education and clinical application within the international orthopaedic and trauma communities. Orthopaedics and Trauma Queensland develops and promotes the innovative use of engineering and technology, in collaboration with surgeons, to provide new techniques, materials, procedures and medical devices. Its integration with clinical practice and strong links with hospitals ensure that the research will be translated into practical outcomes for patients. The group undertakes clinical practice in orthopaedics and trauma and applies core engineering skills to challenges in medicine. The research is built on a strong foundation of knowledge in biomedical engineering, and incorporates expertise in cell biology, mathematical modelling, human anatomy and physiology and clinical medicine in orthopaedics and trauma. New knowledge is being developed and applied to the full range of orthopaedic diseases and injuries, such as knee and hip replacements, fractures and spinal deformities.

Cement-in-cement revision for selected Vancouver Type B1 femoral periprosthetic fractures : A biomechanical analysis

The aim of this study was to perform a biomechanical analysis of the cement-in-cement (c-in-c) technique for fixation of selected Vancouver Type B1 femoral periprosthetic fractures and to assess the degree of cement interposition at the fracture site. Six embalmed cadaveric femora were implanted with a cemented femoral stem. Vancouver Type B1 fractures were created by applying a combined axial and rotational load to failure. The femora were repaired using the c-in-c technique and reloaded to failure. The mean primary fracture torque was 117 Nm (SD 16.6, range 89–133). The mean revision fracture torque was 50 Nm (SD 16.6, range 29–74), which is above the torque previously observed for activities of daily living. Cement interposition at the fracture site was found to be minimal.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

ADCS reaches adulthood : an analysis of the conference and its community over the last eighteen years

How influential is the Australian Document Computing Symposium (ADCS)? What do ADCS articles speak about and who cites them? Who is the ADCS community and how has it evolved? This paper considers eighteen years of ADCS, investigating both the conference and its community. A content analysis of the proceedings uncovers the diversity of topics covered in ADCS and how these have changed over the years. Citation analysis reveals the impact of the papers. The number of authors and where they originate from reveal who has contributed to the conference. Finally, we generate co-author networks which reveal the collaborations within the community. These networks show how clusters of researchers form, the effect geographic location has on collaboration, and how these have evolved over time.

Periprosthetic fracture torque for short versus standard cemented hip stems : an experimental in vitro study

In an attempt to preserve proximal femoral bone stock and achieve a better fit in smaller femora, especially in the Asian population, several new shorter stem designs have become available. We investigated the torque to periprosthetic femoral fracture of the Exeter short stem compared with the conventional length Exeter stem in a Sawbone model. 42 stems; 21 shorter and 21 conventional stems both with three different offsets were cemented in a composite Sawbone model and torqued to fracture. Results showed that Sawbone femurs break at a statistically significantly lower torque to failure with a shorter compared to conventional length Exeter stem of the same offset. Both standard and short stem designs are safe to use as the torque to failure is 7-10 times that seen in activities of daily living.

Comparison of mechanical and ultrasound elastic modulus of ovine tibial cortical bone

Finite element models of bones can be created by deriving geometry from anx-ray CT scan. Material properties such as the elastic modulus can then be applied using either a single or set of homogeneous values, or individual elements can have local values mapped onto them. Values for the elastic modulus can be derived from the CT density values using an elasticityversus density relationship. Many elasticity–density relationships have been reported in the literature for human bone. However, while ovine in vivo models are common in orthopaedic research, no work has been done to date on creating FE models of ovine bones. To create these models and apply relevant material properties, an ovine elasticity-density relationship needs to be determined. Using fresh frozen ovine tibias the apparent density of regions of interest was determined from a clinical CT scan. The bones were the sectioned into cuboid samples of cortical bone from the regions of interest. Ultrasound was used to determine the elastic modulus in each of three directions – longitudinally, radially and tangentially. Samples then underwent traditional compression testing in each direction. The relationships between apparent density and both ultrasound, and compression modulus in each directionwere determined. Ultrasound testing was found to be a highly repeatable non-destructive method of calculating the elastic modulus, particularly suited to samples of this size. The elasticity-density relationships determined in the longitudinal direction were very similar between the compression and ultrasound data over the density range examined.A clear difference was seen in the elastic modulus between the longitudinal and transverse directions of the bone samples, and a transverse elasticity-density relationship is also reported.

Molecular network analysis using reverse phase protein microarrays for patient tailored therapy.

The practice of medicine has always aimed at individualized treatment of disease. The relationship between patient and physician has always been a personal one, and the physician's choice of treatment has been intended to be the best fit for the patient's needs. The necessary pooling/grouping of disease families and their assignment to a number of drugs or treatment methods has, consequently, led to an increase in the number of effective therapies. However, given the heterogeneity of most human diseases, and cancer specifically, it is currently impossible for the treating clinician to effectively predict a patient's response and outcome based on current technologies, much less the idiosyncratic resistances and adverse effects associated with the limited therapeutic options.

Proteins, drug targets and the mechanisms they control : the simple truth about complex networks

Realizing the promise of molecularly targeted inhibitors for cancer therapy will require a new level of knowledge about how a drug target is wired into the control circuitry of a complex cellular network. Here we review general homeostatic principles of cellular networks that enable the cell to be resilient in the face of molecular perturbations, while at the same time being sensitive to subtle input signals. Insights into such mechanisms may facilitate the development of combination therapies that take advantage of the cellular control circuitry, with the aim of achieving higher efficacy at a lower drug dosage and with a reduced probability of drug-resistance development.

Mathematical modeling of the cancer cell’s control circuitry : paving the way to individualized therapeutic strategies

Cancer is a disease of signal transduction in which the dysregulation of the network of intracellular and extracellular signaling cascades is sufficient to thwart the cells finely-tuned biochemical control mechanisms. A keen interest in the mathematical modeling of cell signaling networks and the regulation of signal transduction has emerged in recent years, and has produced a glimmer of insight into the sophisticated feedback control and network regulation operating within cells. In this review, we present an overview of published theoretical studies on the control aspects of signal transduction, emphasizing the role and importance of mechanisms such as ‘ultrasensitivity’ and feedback loops. We emphasize that these exquisite and often subtle control strategies represent the key to orchestrating ‘simple’ signaling behaviors within the complex intracellular network, while regulating the trade-off between sensitivity and robustness to internal and external perturbations. Through a consideration of these apparent paradoxes, we explore how the basic homeostasis of the intracellular signaling network, in the face of carcinogenesis, can lead to neoplastic progression rather than cell death. A simple mathematical model is presented, furnishing a vivid illustration of how ‘control-oriented’ models of the deranged signaling networks in cancer cells may enucleate improved treatment strategies, including patient-tailored combination therapies, with the potential for reduced toxicity and more robust and potent antitumor activity.

Development of reverse phase protein microarrays for clinical applications and patient-tailored therapy

While genomics provide important information about the somatic genetic changes, and RNA transcript profiling can reveal important expression changes that correlate with outcome and response to therapy, it is the proteins that do the work in the cell. At a functional level, derangements within the proteome, driven by post-translational and epigenetic modifications, such as phosphorylation, is the cause of a vast majority of human diseases. Cancer, for instance, is a manifestation of deranged cellular protein molecular networks and cell signaling pathways that are based on genetic changes at the DNA level. Importantly, the protein pathways contain the drug targets in signaling networks that govern overall cellular survival, proliferation, invasion and cell death. Consequently, the promise of proteomics resides in the ability to extend analysis beyond correlation to causality. A critical gap in the information knowledge base of molecular profiling is an understanding of the ongoing activity of protein signaling in human tissue: what is activated and “in use” within the human body at any given point in time. To address this gap, we have invented a new technology, called reverse phase protein microarrays, that can generate a functional read-out of cell signaling networks or pathways for an individual patient obtained directly from a biopsy specimen. This “wiring diagram” can serve as the basis for both, selection of a therapy and patient stratification.

Phosphoprotein pathway mapping: Akt/Mammalian target of rapamycin activation is negatively associated with childhood rhabdomyosarcoma survival

Mapping of protein signaling networks within tumors can identify new targets for therapy and provide a means to stratify patients for individualized therapy. Despite advances in combination chemotherapy, the overall survival for childhood rhabdomyosarcoma remains ∼60%. A critical goal is to identify functionally important protein signaling defects associated with treatment failure for the 40% nonresponder cohort. Here, we show, by phosphoproteomic network analysis of microdissected tumor cells, that interlinked components of the Akt/mammalian target of rapamycin (mTOR) pathway exhibited increased levels of phosphorylation for tumors of patients with short-term survival. Specimens (n = 59) were obtained from the Children's Oncology Group Intergroup Rhabdomyosarcoma Study (IRS) IV, D9502 and D9803, with 12-year follow-up. High phosphorylation levels were associated with poor overall and poor disease-free survival: Akt Ser473 (overall survival P < 0.001, recurrence-free survival P < 0.0009), 4EBP1 Thr37/46 (overall survival P < 0.0110, recurrence-free survival P < 0.0106), eIF4G Ser1108 (overall survival P < 0.0017, recurrence-free survival P < 0.0072), and p70S6 Thr389 (overall survival P < 0.0085, recurrence-free survival P < 0.0296). Moreover, the findings support an altered interrelationship between the insulin receptor substrate (IRS-1) and Akt/mTOR pathway proteins (P < 0.0027) for tumors from patients with poor survival. The functional significance of this pathway was tested using CCI-779 in a mouse xenograft model. CCI-779 suppressed phosphorylation of mTOR downstream proteins and greatly reduced the growth of two different rhabdomyosarcoma (RD embryonal P = 0.00008; Rh30 alveolar P = 0.0002) cell lines compared with controls. These results suggest that phosphoprotein mapping of the Akt/mTOR pathway should be studied further as a means to select patients to receive mTOR/IRS pathway inhibitors before administration of chemotherapy.

A control theoretic paradigm for cell signaling networks : a simple complexity for a sensitive robustness

The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.