Board age and gender diversity : a test of competing linear and curvilinear predictions

The inconsistent findings of past board diversity research demand a test of competing linear and curvilinear diversity–performance predictions. This research focuses on board age and gender diversity, and presents a positive linear prediction based on resource dependence theory, a negative linear prediction based on social identity theory, and an inverted U-shaped curvilinear prediction based on the integration of resource dependence theory with social identity theory. The predictions were tested using archival data on 288 large organizations listed on the Australian Securities Exchange, with a 1-year time lag between diversity (age and gender) and performance (employee productivity and return on assets). The results indicate a positive linear relationship between gender diversity and employee productivity, a negative linear relationship between age diversity and return on assets, and an inverted U-shaped curvilinear relationship between age diversity and return on assets. The findings provide additional evidence on the business case for board gender diversity and refine the business case for board age diversity.

A simplified approach for calculating the moments of action for linear reaction-diffusion equations

The mean action time is the mean of a probability density function that can be interpreted as a critical time, which is a finite estimate of the time taken for the transient solution of a reaction-diffusion equation to effectively reach steady state. For high-variance distributions, the mean action time under-approximates the critical time since it neglects to account for the spread about the mean. We can improve our estimate of the critical time by calculating the higher moments of the probability density function, called the moments of action, which provide additional information regarding the spread about the mean. Existing methods for calculating the nth moment of action require the solution of n nonhomogeneous boundary value problems which can be difficult and tedious to solve exactly. Here we present a simplified approach using Laplace transforms which allows us to calculate the nth moment of action without solving this family of boundary value problems and also without solving for the transient solution of the underlying reaction-diffusion problem. We demonstrate the generality of our method by calculating exact expressions for the moments of action for three problems from the biophysics literature. While the first problem we consider can be solved using existing methods, the second problem, which is readily solved using our approach, is intractable using previous techniques. The third problem illustrates how the Laplace transform approach can be used to study coupled linear reaction-diffusion equations.

Proof of concept : A bioinformatic and serological screening method for identifying new peptide antigens for Chlamydia trachomatis related sequelae in women

This study aimed to identify new peptide antigens from Chlamydia (C.) trachomatis in a proof of concept approach which could be used to develop an epitope-based serological diagnostic for C. trachomatis related infertility in women. A bioinformatics analysis was conducted examining several immunodominant proteins from C. trachomatis to identify predicted immunoglobulin epitopes unique to C. trachomatis. A peptide array of these epitopes was screened against participant sera. The participants (all female) were categorized into the following cohorts based on their infection and gynecological history; acute (single treated infection with C. trachomatis), multiple (more than one C. trachomatis infection, all treated), sequelae (PID or tubal infertility with a history of C. trachomatis infection), and infertile (no history of C. trachomatis infection and no detected tubal damage). The bioinformatics strategy identified several promising epitopes. Participants who reacted positively in the peptide 11 ELISA were found to have an increased likelihood of being in the sequelae cohort compared to the infertile cohort with an odds ratio of 16.3 (95% c.i. 1.65 – 160), with 95% specificity and 46% sensitivity (0.19-0.74). The peptide 11 ELISA has the potential to be further developed as a screening tool for use during the early IVF work up and provides proof of concept that there may be further peptide antigens which could be identified using bioinformatics and screening approaches.

Comparative study on the protective effects of Yinchenhao Decoction against liver injury induced by alpha-naphthylisothiocyanate and carbon tetrachloride

OBJECTIVE: To optimize the animal model of liver injury that can properly represent the pathological characteristics of dampness-heat jaundice syndrome of traditional Chinese medicine. METHODS: The liver injury in the model rat was induced by alpha-naphthylisothiocyanate (ANIT) and carbon tetrachloride (CCl(4) ) respectively, and the effects of Yinchenhao Decoction (, YCHD), a proved effective Chinese medical formula for treating the dampness-heat jaundice syndrome in clinic, on the two liver injury models were evaluated by analyzing the serum level of alanine aminotransferase (ALT), asparate aminotransferase (AST), alkaline phosphatase (ALP), malondialchehyche (MDA), total bilirubin (T-BIL), superoxide dismutase (SOD), glutathione peroxidase (GSH-PX) as well as the ratio of liver weight to body weight. The experimental data were analyzed by principal component analytical method of pattern recognition. RESULTS: The ratio of liver weight to body weight was significantly elevated in the ANIT and CCl(4) groups when compared with that in the normal control (P<0.01). The contents of ALT and T-BIL were significantly higher in the ANIT group than in the normal control (P<0.05,P<0.01), and the levels of AST, ALT and ALP were significantly elevated in CCl(4) group relative to those in the normal control P<0.01). In the YCHD group, the increase in AST, ALT and ALP levels was significantly reduced (P<0.05, P<0.01), but with no significant increase in serum T-BIL. In the CCl(4) intoxicated group, the MDA content was significantly increased and SOD, GSH-PX activities decreased significantly compared with those in the normal control group, respectively (P<0.01). The increase in MDA induced by CCl(4) was significantly reduced by YCHD P<0.05). CONCLUSION: YCHD showed significant effects on preventing liver injury progression induced by CCl(4), and the closest or most suitable animal model for damp-heat jaundice syndrome may be the one induced by CCl(4).

Formation of nanostructured porous Cu-Au surfaces : the influence of cationic sites on (electro)-catalysis

The fabrication of nanostructured bimetallic materials through electrochemical routes offers the ability to control the composition and shape of the final material that can then be effectively applied as (electro)-catalysts. In this work a clean and transitory hydrogen bubble templating method is employed to generate porous Cu–Au materials with a highly anisotropic nanostructured interior. Significantly, the co-electrodeposition of copper and gold promotes the formation of a mixed bimetallic oxide surface which does not occur at the individually electrodeposited materials. Interestingly, the surface is dominated by Au(I) oxide species incorporated within a Cu2O matrix which is extremely effective for the industrially important (electro)-catalytic reduction of 4-nitrophenol. It is proposed that an aurophilic type of interaction takes place between both oxidized gold and copper species which stabilizes the surface against further oxidation and facilitates the binding of 4-nitrophenol to the surface and increases the rate of reaction. An added benefit is that very low gold loadings are required typically less than 2 wt% for a significant enhancement in performance to be observed. Therefore the ability to create a partially oxidized Cu–Au surface through a facile electrochemical route that uses a clean template consisting of only hydrogen bubbles should be of benefit for many more important reactions.

Risk factors for ocular surface squamous neoplasia recurrence after treatment with topical mitomycin C and interferon alpha-2b

Purpose To determine the rate of recurrence and associated risk factors following the use of mitomycin C (MMC) and/or interferon alpha-2b (IFN) for management of non-invasive ocular surface squamous neoplasia (OSSN). Design Retrospective non-comparative interventional case series. Methods Clinical practice setting of 135 patients treated consecutively with topical MMC (0.4 mg/mL) and/or IFN (1 million units/mL) for OSSN observed for clinical recurrence. Results Clinical recurrences were diagnosed in 19 of 135 (14.1%) eyes following topical treatment. The mean time to recurrence was 17.2 months (range 4 - 61) with 14 (73.7%) recurring within a two year period. There was no greater risk of recurrence identified for variables including lesion size, lesion location, gender, age, treatment type or duration. Post-hoc log-Rank pairwise comparisons revealed that lesions initially treated using surgery alone had significantly reduced time to recurrence (21.1 ± 5.6 months) compared to previous topical treatment with MMC (with or without surgery) (29.6 ± 4.7 months) (p = 0.04) and primary OSSN (23.2 ± 1.8 months) (p = 0.09). Conclusions Topical MMC and IFN are an effective treatment modality for a wide range of non-invasive OSSN. Topical therapy avoids the morbidity of excisional surgery with equivalent or reduced recurrence rates and should be considered as primary therapy.

Block models for improved earthwork allocation planning in linear infrastructure construction

Earthwork planning has been considered in this article and a generic block partitioning and modelling approach has been devised to provide strategic plans of various levels of detail. Conceptually this approach is more accurate and comprehensive than others, for instance those that are section based. In response to environmental concerns the metric for decision making was fuel consumption and emissions. Haulage distance and gradient are also included as they are important components of these metrics. Advantageously the fuel consumption metric is generic and captures the physical difficulties of travelling over inclines of different gradients, that is consistent across all hauling vehicles. For validation, the proposed models and techniques have been applied to a real world road project. The numerical investigations have demonstrated that the models can be solved with relatively little CPU time. The proposed block models also result in solutions of superior quality, i.e. they have reduced fuel consumption and cost. Furthermore the plans differ considerably from those based solely upon a distance based metric thus demonstrating a need for industry to reflect upon their current practices.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Higher-order non-linear analysis of steel structures. Part I : elastic second-order formulation

This paper presents a higher-order beam-column formulation that can capture the geometrically non-linear behaviour of steel framed structures which contain a multiplicity of slender members. Despite advances in computational frame software, analyses of large frames can still be problematic from a numerical standpoint and so the intent of the paper is to fulfil a need for versatile, reliable and efficient non-linear analysis of general steel framed structures with very many members. Following a comprehensive review of numerical frame analysis techniques, a fourth-order element is derived and implemented in an updated Lagrangian formulation, and it is able to predict flexural buckling, snap-through buckling and large displacement post-buckling behaviour of typical structures whose responses have been reported by independent researchers. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. The higher-order element forms a basis for augmenting the geometrically non-linear approach with material non-linearity through the refined plastic hinge methodology described in the companion paper.

Higher-order non-linear analysis of steel structures. Part II : refined plastic hinge formulation

In the companion paper, a fourth-order element formulation in an updated Lagrangian formulation was presented to handle geometric non-linearities. The formulation of the present paper extends this to include material non-linearity by proposing a refined plastic hinge approach to analyse large steel framed structures with many members, for which contemporary algorithms based on the plastic zone approach can be problematic computationally. This concept is an advancement of conventional plastic hinge approaches, as the refined plastic hinge technique allows for gradual yielding, being recognized as distributed plasticity across the element section, a condition of full plasticity, as well as including strain hardening. It is founded on interaction yield surfaces specified analytically in terms of force resultants, and achieves accurate and rapid convergence for large frames for which geometric and material non-linearity are significant. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. In addition to the numerical efficiency, the present versatile approach is able to capture different kinds of material and geometric non-linearities on general applications of steel structures, and thereby it offers an efficacious and accurate means of assessing non-linear behaviour of the structures for engineering practice.

Interleukin-1beta induces human proximal tubule cell injury, alpha-smooth muscle actin expression and fibronectin production

BACKGROUND Tubulointerstitial lesions, characterized by tubular injury, interstitial fibrosis and the appearance of myofibroblasts, are the strongest predictors of the degree and progression of chronic renal failure. These lesions are typically preceded by macrophage infiltration of the tubulointerstitium, raising the possibility that these inflammatory cells promote progressive renal disease through fibrogenic actions on resident tubulointerstitial cells. The aim of the present study, therefore, was to investigate the potentially fibrogenic mechanisms of interleukin-1beta (IL-1beta), a macrophage-derived pro-inflammatory cytokine, on human proximal tubule cells (PTC). METHODS Confluent, quiescent, passage 2 PTC were established in primary culture from histologically normal segments of human renal cortex (N = 11) and then incubated in serum- and hormone-free media supplemented with either IL-1beta (0 to 4 ng/mL) or vehicle (control). RESULTS IL-1beta significantly enhanced fibronectin secretion by up to fourfold in a time- and concentration-dependent fashion. This was accompanied by significant (2.5- to 6-fold) increases in alpha-smooth muscle actin (alpha-SMA) expression, transforming growth factor beta (TGF-beta1) secretion, nitric oxide (NO) production, NO synthase 2 (NOS2) mRNA and lactate dehydrogenase (LDH) release. Cell proliferation was dose-dependently suppressed by IL-1beta. NG-methyl-l-arginine (L-NMMA; 1 mmol/L), a specific inhibitor of NOS, blocked NO production but did not alter basal or IL-1beta-stimulated fibronectin secretion. In contrast, a pan-specific TGF-beta neutralizing antibody significantly blocked the effects of IL-1beta on PTC fibronectin secretion (IL-1beta, 268.1 +/- 30.6 vs. IL-1beta+alphaTGF-beta 157.9 +/- 14.4%, of control values, P < 0.001) and DNA synthesis (IL-1beta 81.0 +/- 6.7% vs. IL-1beta+alphaTGF-beta 93.4 +/- 2.1%, of control values, P < 0.01). CONCLUSION IL-1beta acts on human PTC to suppress cell proliferation, enhance fibronectin production and promote alpha-smooth muscle actin expression. These actions appear to be mediated by a TGF-beta1 dependent mechanism and are independent of nitric oxide release.

Capturing complex, non-linear team behaviours during competitive football performance

This study investigated changes in the complexity (magnitude and structure of variability) of the collective behaviours of association football teams during competitive performance. Raw positional data from an entire competitive match between two professional teams were obtained with the ProZone® tracking system. Five compound positional variables were used to investigate the collective patterns of performance of each team including: surface area, stretch index, team length, team width, and geometrical centre. Analyses involve the coefficient of variation (%CV) and approximate entropy (ApEn), as well as the linear association between both parameters. Collective measures successfully captured the idiosyncratic behaviours of each team and their variations across the six time periods of the match. Key events such as goals scored and game breaks (such as half time and full time) seemed to influence the collective patterns of performance. While ApEn values significantly decreased during each half, the %CV increased. Teams seem to become more regular and predictable, but with increased magnitudes of variation in their organisational shape over the natural course of a match.

Comparison of high level FPGA hardware design for solving tri-diagonal linear systems

Reconfigurable computing devices can increase the performance of compute intensive algorithms by implementing application specific co-processor architectures. The power cost for this performance gain is often an order of magnitude less than that of modern CPUs and GPUs. Exploiting the potential of reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) is typically a complex and tedious hardware engineering task. Re- cently the major FPGA vendors (Altera, and Xilinx) have released their own high-level design tools, which have great potential for rapid development of FPGA based custom accelerators. In this paper, we will evaluate Altera’s OpenCL Software Development Kit, and Xilinx’s Vivado High Level Sythesis tool. These tools will be compared for their per- formance, logic utilisation, and ease of development for the test case of a Tri-diagonal linear system solver.

Preliminary characterisation of tumor necrosis factor alpha and interleukin-10 responses to chlamydia pecorum infection in the koala (Phascolarctos cinereus)

Debilitating infectious diseases caused by Chlamydia are major contributors to the decline of Australia's iconic native marsupial species, the koala (Phascolarctos cinereus). An understanding of koala chlamydial disease pathogenesis and the development of effective strategies to control infections continue to be hindered by an almost complete lack of species-specific immunological reagents. The cell-mediated immune response has been shown to play an influential role in the response to chlamydial infection in other hosts. The objective of this study, hence, was to provide preliminary data on the role of two key cytokines, pro-inflammatory tumour necrosis factor alpha (TNFα) and anti-inflammatory interleukin 10 (IL10), in the koala Chlamydia pecorum response. Utilising sequence homology between the cytokine sequences obtained from several recently sequenced marsupial genomes, this report describes the first mRNA sequences of any koala cytokine and the development of koala specific TNFα and IL10 real-time PCR assays to measure the expression of these genes from koala samples. In preliminary studies comparing wild koalas with overt chlamydial disease, previous evidence of C. pecorum infection or no signs of C. pecorum infection, we revealed strong but variable expression of TNFα and IL10 in wild koalas with current signs of chlamydiosis. The description of these assays and the preliminary data on the cell-mediated immune response of koalas to chlamydial infection paves the way for future studies characterising the koala immune response to a range of its pathogens while providing reagents to assist with measuring the efficacy of ongoing attempts to develop a koala chlamydial vaccine.

Detecting and Analyzing Linear Structures in Biomedical Images : A Case Study Using Corneal Nerve Fibers

Diabetic peripheral neuropathy (DPN) is one of the most common long-term complications of diabetes. The accurate detection and quantification of DPN are important for defining at-risk patients, anticipating deterioration, and assessing new therapies. Current methods of detecting and quantifying DPN, such as neurophysiology, lack sensitivity, require expert assessment and focus primarily on large nerve fibers. However, the earliest damage to nerve fibers in diabetic neuropathy is to the small nerve fibers. At present, small nerve fiber damage is currently assessed using skin/nerve biopsy; both are invasive technique and are not suitable for repeated investigations.