The employment effects of gender discrimination in Australia 1994-95

Interpreting the unexplained component of the gender wage gap as indicative of discrimination, the empirical literature to date has tended to ignore the potential impact wage discrimination may have on employment. Clearly, employment effects will arise if discrimination lowers the female offered wage and the labour supply curve is upward sloping. The empirical analysis employs the ABS Income Distribution Survey 1994–95 and finds evidence of both wage and associated employment effects. The analysis is replicated for the earlier period 1989–90. A comparison across time is of interest given the substantial deregulation of the Australian labour market over the period.

Are employment effects of gender discrimination important? Some evidence from Great Britain

Interpreting the unexplained component of the gender wage gap as indicative of discrimination, the empirical literature to date has tended to ignore the potential impact wage discrimination may have on employment. Employment effects may arise if discrimination lowers the female offered wage and the labour supply curve is upward sloping. The empirical analysis employs the British Household Panel Study and finds evidence of both wage and associated employment effects.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

A sequential Monte Carlo framework for adaptive Bayesian model discrimination designs using mutual information

In this paper we present a unified sequential Monte Carlo (SMC) framework for performing sequential experimental design for discriminating between a set of models. The model discrimination utility that we advocate is fully Bayesian and based upon the mutual information. SMC provides a convenient way to estimate the mutual information. Our experience suggests that the approach works well on either a set of discrete or continuous models and outperforms other model discrimination approaches.

Electrocoagulation as a pre-treatment stage to reverse osmosis units

Reverse osmosis (RO) is used by coal seam gas (CSG) operators to treat produced water as it is a well-established and proven technology worldwide. Despite the suitability of RO, there are problems associated with RO technology such as membrane fouling which although not preventing use of RO does decrease effectiveness and increase operating costs. Hence, effective pre-treatment of water samples is essential. Electrocoagulation (EC) potentially can provide improved water purification compared to conventional coagulation prior to an RO unit. This paper provides the first reported study of EC for CSG water pre-treatment and compares the performance to a range of aluminium and iron based coagulants. It was found that EC was superior in terms of removal of silica, calcium, magnesium, barium and strontium in the produced water.

Improved healing of large segmental defects in the rat femur by reverse dynamization in the presence of bone morphogenetic protein-2

Background Large segmental defects in bone do not heal well and present clinical challenges. This study investigated modulation of the mechanical environment as a means of improving bone healing in the presence of bone morphogenetic protein (BMP)-2. Although the influence of mechanical forces on the healing of fractures is well established, no previous studies, to our knowledge, have described their influence on the healing of large segmental defects. We hypothesized that bone-healing would be improved by initial, low-stiffness fixation of the defect, followed by high-stiffness fixation during the healing process. We call this reverse dynamization. Methods A rat model of a critical-sized femoral defect was used. External fixators were constructed to provide different degrees of stiffness and, importantly, the ability to change stiffness during the healing process in vivo. Healing of the critical-sized defects was initiated by the implantation of 11 mg of recombinant human BMP (rhBMP)-2 on a collagen sponge. Groups of rats receiving BMP-2 were allowed to heal with low, medium, and high-stiffness fixators, as well as under conditions of reverse dynamization, in which the stiffness was changed from low to high at two weeks. Healing was assessed at eight weeks with use of radiographs, histological analysis, microcomputed tomography, dual x-ray absorptiometry, and mechanical testing. Results Under constant stiffness, the low-stiffness fixator produced the best healing after eight weeks. However, reverse dynamization provided considerable improvement, resulting in a marked acceleration of the healing process by all of the criteria of this study. The histological data suggest that this was the result of intramembranous, rather than endochondral, ossification. Conclusions Reverse dynamization accelerated healing in the presence of BMP-2 in the rat femur and is worthy of further investigation as a means of improving the healing of large segmental bone defects. Clinical Relevance These data provide the basis of a novel, simple, and inexpensive way to improve the healing of critical-sized defects in long bones. Reverse dynamization may also be applicable to other circumstances in which bonehealing is problematic.

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.

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.

Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma

Cancer can be defined as a deregulation or hyperactivity in the ongoing network of intracellular and extracellular signaling events. Reverse phase protein microarray technology may offer a new opportunity to measure and profile these signaling pathways, providing data on post-translational phosphorylation events not obtainable by gene microarray analysis. Treatment of ovarian epithelial carcinoma almost always takes place in a metastatic setting since unfortunately the disease is often not detected until later stages. Thus, in addition to elucidation of the molecular network within a tumor specimen, critical questions are to what extent do signaling changes occur upon metastasis and are there common pathway elements that arise in the metastatic microenvironment. For individualized combinatorial therapy, ideal therapeutic selection based on proteomic mapping of phosphorylation end points may require evaluation of the patient's metastatic tissue. Extending these findings to the bedside will require the development of optimized protocols and reference standards. We have developed a reference standard based on a mixture of phosphorylated peptides to begin to address this challenge.

Calculation of the oxygen isotope discrimination factor for studying plant respiration

Measurement of discrimination against 18O during dark respiration in plants is currently accepted as the only reliable method of estimating the partitioning of electrons between the cytochrome and alternative pathways. In this paper, we review the theory of the technique and its application to a gas-phase system. We extend it to include sampling effects and show that the isotope discrimination factor, D, is calculated as –dln(1 + δ)/dlnO*, where δ is isotopic composition of the substrate oxygen and O*=[O2]/[N2] in a closed chamber containing tissue respiring in the dark. It is not necessary to integrate the expression but, if the integrated form is used, the resultant regression should not be constrained through the origin. This is important since any error in D will have significant effects on the estimation of the flux of electrons through the two pathways.