Public finance and income redistribution in interwar Australia: towards a class analysis

In this paper I focus on a neglected aspect of Australian political history, the extent to which Australian governments actually redistributed income. The German sociologist Rudolf Goldscheid argued that 'the budget is the skeleton of the state stripped of all misleading ideologies'. In Australia a party that claimed to represent lower income earners, the Labor Party, was a major political force, but did Labor actually make a difference to the distribution of income across social classes, or did Labor's rhetoric of equity merely serve to incorporate workers into the capitalist system? A quantitative approach to the political history of labour may enable us to escape both nostalgia for old labourism (which the Howard years have encouraged) and a simple and undifferentiated rejection of labourism as a reformist agent of social integration.

This paper incorporates some material from a 2005 paper that examined overall expenditure patterns and taxation patterns across the states and Commonwealth from 1910 to 1940 but it goes beyond the aggregate approach of this paper to consider the extent which the varying patterns of taxation and public expenditure across Australia impacted on different social classes during the 1930s. It is very much a preliminary analysis based on existing compilations of taxation statistics. It is a static analysis and does not consider if nominally redistributive taxation and expenditure patterns might be rendered ineffective by consequent interstate migration.

Experimental and numerical analysis of the deformed process of cracks/cavities

In this paper, the three-point bending tests of beams with a small single-edge crack are conducted to demonstrate the reliability and accuracy of the laser diffraction technique in detecting its deformation and evolution. As a comparison, the quasi-static analysis of the beam subjected to 3-point bending is further proceeded using the finite element method and the related results have been in good agreement with those from the tests.

Analysis of dynamic strains in tibia during human locomotion based on flexible multibody approach integrated with magnetic resonance imaging technique

Bone is known to adapt to the prevalent strain environment while the variation in strains, e.g., due to mechanical loading, modulates bone remodeling, and modeling. Dynamic strains rather than static strains provide the primary stimulus of bone functional adaptation. The finite element method can be generally used for estimating bone strains, but it may be limited to the static analysis of bone strains since the dynamic analysis requires expensive computation. Direct in vivo strain measurement, in turn, is an invasive procedure, limited to certain superficial bone sites, and requires surgical implementation of strain gauges and thus involves risks (e.g., infection). Therefore, to overcome difficulties associated with the finite element method and the in vivo strain measurements, the flexible multibody simulation approach has been recently introduced as a feasible method to estimate dynamic bone strains during physical activity. The purpose of the present study is to further strengthen the idea of using the flexible multibody approach for the analysis of dynamic bone strains. Besides discussing the background theory, magnetic resonance imaging is integrated into the flexible multibody approach framework so that the actual bone geometry could be better accounted for and the accuracy of prediction improved.

The effect of osteoporotic vertebral fracture of predicted spinal loads in vivo

he aetiology of osteoporotic vertebral fractures is multi-factorial, and cannot be explained solely by low bone mass. After sustaining an initial vertebral fracture, the risk of subsequent fracture increases greatly. Examination of physiologic loads imposed on vertebral bodies may help to explain a mechanism underlying this fracture cascade. This study tested the hypothesis that model-derived segmental vertebral loading is greater in individuals who have sustained an osteoporotic vertebral fracture compared to those with osteoporosis and no history of fracture. Flexion moments, and compression and shear loads were calculated from T2 to L5 in 12 participants with fractures (66.4 ± 6.4 years, 162.2 ± 5.1 cm, 69.1 ± 11.2 kg) and 19 without fractures (62.9 ± 7.9 years, 158.3 ± 4.4 cm, 59.3 ± 8.9 kg) while standing. Static analysis was used to solve gravitational loads while muscle-derived forces were calculated using a detailed trunk muscle model driven by optimization with a cost function set to minimise muscle fatigue. Least squares regression was used to derive polynomial functions to describe normalised load profiles. Regression co-efficients were compared between groups to examine differences in loading profiles. Loading at the fractured level, and at one level above and below, were also compared between groups. The fracture group had significantly greater normalised compression (p = 0.0008) and shear force (p < 0.0001) profiles and a trend for a greater flexion moment profile. At the level of fracture, a significantly greater flexion moment (p = 0.001) and shear force (p < 0.001) was observed in the fracture group. A greater flexion moment (p = 0.003) and compression force (p = 0.007) one level below the fracture, and a greater flexion moment (p = 0.002) and shear force (p = 0.002) one level above the fracture was observed in the fracture group. The differences observed in multi-level spinal loading between the groups may explain a mechanism for increased risk of subsequent vertebral fractures. Interventions aimed at restoring vertebral morphology or reduce thoracic curvature may assist in normalising spine load profiles.

Effects of design parameters on sensitivity of microcantilever biosensors

Microcantilever biosensors produce cantilever bending due to differential surface stress between upper and lower surfaces of the cantilever. The bending is associated with concentration of ligands and adsorbed ligand-receptor intermolecular forces. Sample volume sizes in clinical diagnostic applications are usually very minute requiring a highly sensitive microcantilever for disease detection. This paper investigates a number of parameters that influence the sensitivity of microcantilever biosensors. The parameters include length, thickness, shape, and material of the cantilever beam. Biosensors of varying parameters are modeled and simulated. The results show that increasing the length of the cantilever beam enhances its sensitivity. However, increasing the thickness of the cantilever beam reduces its sensitivity. In static analysis, the shape of the cantilever beam does not notably impact upon its sensitivity. Also, using materials with lower Young’s modulus improves the sensitivity.

Malware variant detection using similarity search over sets of control flow graphs

Static detection of polymorphic malware variants plays an important role to improve system security. Control flow has shown to be an effective characteristic that represents polymorphic malware instances. In our research, we propose a similarity search of malware using novel distance metrics of malware signatures. We describe a malware signature by the set of control flow graphs the malware contains. We propose two approaches and use the first to perform pre-filtering. Firstly, we use a distance metric based on the distance between feature vectors. The feature vector is a decomposition of the set of graphs into either fixed size k-sub graphs, or q-gram strings of the high-level source after decompilation. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flow graphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms.

Effects of load modeling in power distribution system with distributed wind generation

This paper presents the impact of different types of load models in distribution network with distributed wind generation. The analysis is carried out for a test distribution system representative of the Kumamoto area in Japan. Firstly, this paper provides static analysis showing the impact of static load on distribution system. Then, it investigates the effects of static as well as composite load based on the load composition of IEEE task force report [1] through an accurate time-domain analysis. The analysis shows that modeling of loads has a significant impact on the voltage dynamics of the distribution system with distributed generation.

Control flow-based malware variant detection

Static detection of malware variants plays an important role in system security and control flow has been shown as an effective characteristic that represents polymorphic malware. In our research, we propose a similarity search of malware to detect these variants using novel distance metrics. We describe a malware signature by the set of control flowgraphs the malware contains. We use a distance metric based on the distance between feature vectors of string-based signatures. The feature vector is a decomposition of the set of graphs into either fixed size k-subgraphs, or q-gram strings of the high-level source after decompilation. We use this distance metric to perform pre-filtering. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flowgraphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms. © 2013 IEEE.

Computational inverse analysis of static recrystallization kinetics

© 2015 Published by Elsevier Ltd. All rights reserved. Accurate static recrystallization (SRX) models are necessary to improve the properties of austenitic steels by thermo-mechanical operations. This relies heavily on a careful and accurate analysis of "the interrupted test data" and conversion of the heterogeneous deformation data to the flow stress. A "computational-experimental inverse method" was presented and implemented here to analyze the SRX test data, which takes into account the heterogeneous softening of the post-interruption test sample. Conventional and "inverse" methods were used to identify the SRX kinetics for a model austenitic steel deformed at 1273 K (with a strain rate of 1 s-1) using the hot torsion test assess the merits of each method. Typical "static recrystallization distribution maps" in the test sample indicated that, at the onset of the second pass deformation with less than a critical holding time and a given pre-strain, a "partially-recrystallized zone" existed in the cylindrical core of the specimen near its center line. For the investigated scenario, the core was confined in the first half of the gauge radius when the holding time and the maximum pre strain were below 29 s and 0.5, respectively. For maximum pre strains smaller than 0.2, the specimen did not fully recrystallize, even at the gauge surface after holding for 50 s. Under such conditions, the conventional methods produced significant error.

Exergaming as a viable therapeutic tool to improve static and dynamic balance among older adults and people with idiopathic Parkinson's disease: a systematic review and meta-analysis

The use of virtual reality games (known as "exergaming") as a neurorehabilitation tool is gaining interest. Therefore, we aim to collate evidence for the effects of exergaming on the balance and postural control of older adults and people with idiopathic Parkinson's disease (IPD). Six electronic databases were searched, from inception to April 2015, to identify relevant studies. Standardized mean differences (SMDs) and 95% confidence intervals (CI) were used to calculate effect sizes between experimental and control groups. I (2) statistics were used to determine levels of heterogeneity. 325 older adults and 56 people with IPD who were assessed across 11 -studies. The results showed that exergaming improved static balance (SMD 1.069, 95% CI 0.563-1.576), postural control (SMD 0.826, 95% CI 0.481-1.170), and dynamic balance (SMD -0.808, 95% CI -1.192 to -0.424) in healthy older adults. Two IPD studies showed an improvement in static balance (SMD 0.124, 95% CI -0.581 to 0.828) and postural control (SMD 2.576, 95% CI 1.534-3.599). Our findings suggest that exergaming might be an appropriate therapeutic tool for improving balance and postural control in older adults, but more -large-scale trials are needed to determine if the same is true for people with IPD.

Court delays and the defendant behaviour: an economic analysis

Court delays are consistently criticised as being inimical to social welfare. However, the theoretical basis for this assertion is not well established in the law and economics literature. As a first step, very little is known about the impact of court delay on the defendant's optimal plea decision. If the defendant is rational in the sense of inter temporally optimising, court delay may increase or decrease the probability of a trial depending on the defendant's bail status. Some empirical support for this theoretical proposition is found using data on plea behaviour for a selection of cases heard in NSW Australia.

An analysis of the transition between strain dependent and independent softening in austenite

The post-deformation softening behaviour of austenite has been studied for various compositions and deformation conditions. The strain at which the transition from strain dependent to strain independent post-deformation softening behaviour occurs (ε*) has been found to coincide closely with the strain to the peak stress (εp) under certain conditions but not under others. It has been proposed that the relationship between ε* and εp may be described geometrically using the initial grain size and the dynamically recrystallised grain size.

Automotive can network response time analysis with variable jitter

Many methods to calculate message latencies for Controller Area Network (CAN) have previously been presented based upon the static worst-case behaviour of the system. With the use of modern simulation tools however, the behaviour of CAN networks can be simulated dynamically in order to find the likely worst-case response times for CAN messages. This paper shows the development of an automotive body control network model to be used as the basis for further simulations. A method to simulate the Worst-Case Response Time of this model is then presented, taking into account random queuing jitter.

Analysis of work hardening and recrystallization during the hot working of steel using a statistically based internal variable model

A mathematical model has been developed which describes the hot deformation and recrystallization behavior of austenite using a single internal variable: dislocation density. The dislocation density is incorporated into equations describing the rate of recovery and recrystallization. In each case no distinction is made between static and dynamic events, and the model is able to simulate multideformation processes. The model is statistically based and tracks individual populations of the dislocation density during the work-hardening and softening phases. After tuning using available data the model gave an accurate prediction of the stress–strain behavior and the static recrystallization kinetics for C–Mn steels. The model correctly predicted the sensitivity of the post deformation recrystallization behavior to process variables such as strain, strain rate and temperature, even though data for this were not explicitly incorporated in the tuning data set. In particular, the post dynamic recrystallization (generally termed metadynamic recrystallization) was shown to be largely independent of strain and temperature, but a strong function of strain rate, as observed in published experimental work.

Dynamic analysis of drug-induced cytotoxicity using chip-based dielectrophoretic cell immobilization technology

Quantification of programmed and accidental cell death provides useful end-points for the anticancer drug efficacy assessment. Cell death is, however, a stochastic process. Therefore, the opportunity to dynamically quantify individual cellular states is advantageous over the commonly employed static, end-point assays. In this work, we describe the development and application of a microfabricated, dielectrophoretic (DEP) cell immobilization platform for the realtime analysis of cancer drug-induced cytotoxicity. Microelectrode arrays were designed to generate weak electro-thermal vortices that support efficient drug mixing and rapid cell immobilization at the delta-shape regions of strong electric field formed between the opposite microelectrodes. We applied this technology to the dynamic analysis of hematopoietic tumor cells that represent a particular challenge for real-time imaging due to their dislodgement during image acquisition. The present study was designed to provide a comprehensive mechanistic rationale for accelerated cell-based assays on DEP chips using real-time labeling with cell permeability markers. In this context, we provide data on the complex behavior of viable vs dying cells in the DEP fields and probe the effects of DEP fields upon cell responses to anticancer drugs and overall bioassay performance. Results indicate that simple DEP cell immobilization technology can be readily applied for the dynamic analysis of investigational drugs in hematopoietic cancer cells. This ability is of particular importance in studying the outcome of patient derived cancer cells, when exposed to therapeutic drugs, as these cells are often rare and difficult to collect, purify and immobilize.