Effects of lime content and amelioration period in double lime application on the strength of lime treated expansive sub-grade soils

The addition of lime into soils has been widely used to stabilize the expansive sub-grade soils when the road pavements are constructed on them. It is common practice to apply a half of the required lime amount and allow a certain time period for lime to react with soils (Amelioration period) before applying the rest of lime and compacting the sub-grade. The optimum amelioration period is essential to minimize the construction delay and to gain the higher strength. In this study, two different expansive soils procured from two different locations in the state of Queensland in Australia were first mixed with different lime contents. A soil mixed with a particular lime content was compacted at different amelioration periods (e.g.: 0, 6, 12, 18, 24 hrs) to obtain soil samples to measure the Unconfined Compressive Strength (UCS). The results suggested that for a given amelioration period, UCS increased with the increase in lime content. The optimum amelioration period could be within 14~17 hours for most of the lime contents in tested soils. This could suggest that the current 24-48 hour amelioration period specified by the Queensland Department of Transport and Main roads could be reduced.

Knee flexor strength and bicep femoris electromyographical activity is lower in previously strained hamstrings

The aim of this study was to determine if athletes with a history of hamstring strain injury display lower levels of surface EMG (sEMG) activity and median power frequency in the previously injured hamstring muscle during maximal voluntary contractions. Recreational athletes were recruited, 13 with a history of unilateral hamstring strain injury and 15 without prior injury. All athletes undertook isokinetic dynamometry testing of the knee flexors and sEMG assessment of the biceps femoris long head (BF) and medial hamstrings (MH) during concentric and eccentric contractions at ± 180 and ± 600.s-1. The knee flexors on the previously injured limb were weaker at all contraction speeds compared to the uninjured limb (+1800.s-1 p = 0.0036; +600.s-1 p = 0.0013; -600.s-1 p = 0.0007; -1800.s-1 p = 0.0007) whilst sEMG activity was only lower in the BF during eccentric contractions (-600.s-1 p = 0.0025; -1800.s-1 p = 0.0003). There were no between limb differences in MH sEMG activity or median power frequency from either BF or MH in the injured group. The uninjured group showed no between limb differences in any of the tested variables. Secondary analysis comparing the between limb difference in the injured and the uninjured groups, confirmed that previously injured hamstrings were mostly weaker (+1800.s-1 p = 0.2208; +600.s-1 p = 0.0379; -600.s-1 p = 0.0312; -1800.s-1 p = 0.0110) and that deficits in sEMG were confined to the BF during eccentric contractions (-600.s-1 p = 0.0542; -1800.s-1 p = 0.0473) Previously injured hamstrings were weaker and BF sEMG activity was lower than the contralateral uninjured hamstring. This has implications for hamstring strain injury prevention and rehabilitation which should consider altered neural function following hamstring strain injury.

Knee flexor strength and biceps femoris activation deficits following hamstring strain injury

Background: Hamstring strain injuries (HSI) are prevalent in sport and re-injury rates have been high for many years. Maladaptation following HSI are implicated in injury recurrence however nervous system function following HSI has received little attention. Aim: To determine if recreational athletes with a history of unilateral HSI, who have returned to training and competition, will exhibit lower levels of voluntary activation (VA) and median power frequency (MPF) in the previously injured limb compared to the uninjured limb at long muscle lengths. Methods: Twenty-eight recreational athletes were recruited. Of these, 13 athletes had a history of unilateral HSI and 15 had no history of HSI. Following familiarisation, all athletes undertook isokinetic dynamometry testing and surface electromyography assessment of the biceps femoris long head and medial hamstrings during concentric and eccentric contractions at ± 180 and ± 60deg/s. Results: The previously injured limb was weaker at all contraction speeds compared to the uninjured limb (+180deg/s mean difference(MD) = 9.3Nm, p = 0.0036; +60deg/s MD = 14.0Nm, p = 0.0013; -60deg/s MD = 18.3Nm, p = 0.0007; -180deg/s MD = 20.5Nm, p = 0.0007) whilst VA was only lower in the biceps femoris long head during eccentric contractions (-60deg/s MD = 0.13, p = 0.0025; -180deg/s MD = 0.13, p = 0.0003). There were no between limb differences in medial hamstring VA or MPF from either biceps femoris long head or medial hamstrings in the injured group. The uninjured group showed no between limb differences with any of the tested variables. Conclusion: Previously injured hamstrings were weaker than the contralateral uninjured hamstring at all tested speeds and contraction modes. During eccentric contractions biceps femoris long head VA was lower in the previously injured limb suggesting neural control of biceps femoris long head may be altered following HSI. Current rehabilitation practices have been unsuccessful in restoring strength and VA following HSI. Restoration of these markers should be considered when determining the success of rehabilitation from HSI. Further investigations are required to elucidate the full impact of lower levels of biceps femoris long head VA following HSI on rehabilitation outcomes and re-injury risk.

Knee extensor strength differences in obese and healthy-weight 10-13 year olds

The purpose of this study was to investigate if obese children have reduced knee extensor (KE) strength and to explore the relationship between adiposity and KE strength. An observational case-control study was conducted in three Australian states, recruiting obese [n=107 (51 female, 56 male)] and healthy-weight [n=132 (56 female, 76 male)] 10–13 year old children. Body mass index, body composition (dual energy X-ray absorptiometry), isokinetic/isometric peak KE torques (dynamometry) and physical activity (accelerometry) were assessed. Results revealed that compared with their healthy-weight peers, obese children had higher absolute KE torques (P≤0.005), equivocal KE torques when allometrically normalized for fat-free mass (FFM) (P≥0.448) but lower relative KE torques when allometrically normalized for body mass (P≤0.008). Adjustments for maternal education, income and accelerometry had little impact on group differences, except for isometric KE torques relative to body mass which were no longer significantly lower in obese children (P≥0.013, not significant after controlling for multiple comparisons). Percent body fat was inversely related to KE torques relative to body mass (r= -0.22 to -0.35, P≤0.002), irrespective of maternal education, income or accelerometry. In conclusion, while obese children have higher absolute KE strength and FFM, they have less functional KE strength (relative to mass) available for weight-bearing activities than healthy-weight children. The finding that FFM-normalized KE torques did not differ suggests that the intrinsic contractile properties of the KE muscles are unaffected by obesity. Future research is needed to see if deficits in KE strength relative to mass translate into functional limitations in weight-bearing activities.

The preferences of private equity investors in selecting target acquisitions : an international investigation

This study investigates the characteristics and attributes that private equity investors prefer when selecting target acquisitions. These characteristics are examined against a matched sample of firms subject to corporate acquisitions via tender/merger offer during 2000-2009, across seven countries: Australia, Canada, the United Kingdom, the USA, France, Germany and Sweden. We show that firm-specific characteristics are more influential in target selection than external or institutional variables. In particular, private equity targets exhibit lower stock volatility and long-term growth prospects, are larger, and have greater abnormal operating income relative to tender/merger offer target firms. Further, private equity bidders exhibit 'home bias', implying that familiarity motivates target selection. Institutional factors remain largely insignificant across all tests.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Experimental studies of the shear behavior and strength of LiteSteel beams with stiffened web openings

Abstract: LiteSteel beam (LSB) is a new cold-formed steel hollow flange channel section produced using a patented manufacturing process. It is commonly used as flexural members in residential, industrial and commercial buildings. Current practice in flooring systems is to include openings in the web element of floor joists or bearers so that building services can be located within them. Test results have shown that the shear capacity of LSBs can be reduced considerably by the inclusion of web openings. A cost effective method of eliminating the detrimental effects of a large web opening is to attach suitable stiffeners around the web openings of LSBs. A detailed experimental study consisting of 17 shear tests was therefore undertaken to investigate the shear behaviour and strength of LSBs with stiffened circular web openings. Both plate and stud stiffeners with varying sizes and thicknesses were attached to the web elements of LSBs using a number of screw-fastening arrangements in order to develop a suitable stiffening arrangement for LSBs. Simply supported test specimens of LSBs with an aspect ratio of 1.5 were loaded at mid-span until failure. This paper presents the details of this experimental study of LSBs with stiffened web openings, and the results of their shear capacities and associated behavioural characteristics. Suitable screw-fastened plate stiffener arrangements have been recommended in order to restore the original shear capacity of LSBs.

Concurrent and longitudinal links between children’s and their friends’ antisocial and prosocial behavior in preschool

Concurrent and longitudinal links between children’s own and their nominated best friends’ antisocial and prosocial behavior were studied in a normative sample of 3–5-year-olds (N = 203). Moderating effects of age and gender were also explored. Subscales of the Strength and Difficulties Questionnaire (SDQ) were used to obtain teacher ratings of behavior for each target child and his/her nominated best friends. Nomination of best friends with higher levels of antisocial behavior and lower levels of prosocial behavior was concurrently linked to more antisocial behavior in boys. Nomination of highly prosocial best friends was concurrently linked to more prosocial behavior in both boys and girls. However, the study found no longitudinal effects of best friends’ behavior on target child’s behavior over a one-year period. A group of children who nominated no best friends at T1 were generally perceived as less prosocial, but not more antisocial, than other children. © 2011 Elsevier Inc. All rights reserved.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

Dynamic lifecycle strategies for target date retirement funds

Target date retirement funds have gained favor with retirement plan investors in recent years. Typically, these funds initially have a high allocation to stocks but move towards less volatile assets, such as bonds and cash, as the target retirement date approaches. Empirical research has generally found that a switch to low-risk assets prior to retirement can reduce the risk of confronting the most extreme negative outcomes. This article questions the rationale for lifecycle switching based solely on age or target retirement date as is the prevalent practice among target date funds. The authors argue that a dynamic switching strategy, which takes into consideration achieved investment returns, will produce superior returns for most investors compared to conventional lifecycle switching. In this article, the authors put forward a dynamic lifecycle switching strategy that is conditional on the attainment of the plan member's wealth accumulation objective at every stage of switching.

Smartphone malware evolution revisited : Android next target?

Smartphones started being targets for malware in June 2004 while malware count increased steadily until the introduction of a mandatory application signing mechanism for Symbian OS in 2006. From this point on, only few news could be read on this topic. Even despite of new emerging smartphone platforms, e.g. android and iPhone, malware writers seemed to lose interest in writing malware for smartphones giving users an unappropriate feeling of safety. In this paper, we revisit smartphone malware evolution for completing the appearance list until end of 2008. For contributing to smartphone malware research, we continue this list by adding descriptions on possible techniques for creating the first malware(s) for Android platform. Our approach involves usage of undocumented Android functions enabling us to execute native Linux application even on retail Android devices. This can be exploited to create malicious Linux applications and daemons using various methods to attack a device. In this manner, we also show that it is possible to bypass the Android permission system by using native Linux applications.

Shear design of cold-formed steel beams using direct strength method

This paper presents the direct strength method (DSM) equations for cold-formed steel beams subject to shear. Light gauge cold-formed steel sections have been developed as more economical building solutions to the alternative heavier hot-rolled sections in the commercial and residential markets. Cold-formed lipped channel beams (LCB), LiteSteel beams (LSB) and hollow flange beams (HFB) are commonly used as flexural members such as floor joists and bearers. However, their shear capacities are determined based on conservative design rules. For the shear design of cold-formed web panels, their elastic shear buckling strength must be determined accurately including the potential post-buckling strength. Currently the elastic shear buckling coefficients of web panels are determined by assuming conservatively that the web panels are simply supported at the junction between the flange and web elements and ignore the post-buckling strength. Hence experimental and numerical studies were conducted to investigate the shear behaviour and strength of LSBs, LCBs and HFBs. New direct strength method (DSM) based design equations were proposed to determine the ultimate shear capacities of cold-formed steel beams. An improved equation for the higher elastic shear buckling coefficient of cold-formed steel beams was proposed based on finite element analysis results and included in the DSM design equations. A new post-buckling coefficient was also introduced in the DSM equation to include the available post-buckling strength of cold-formed steel beams.

Molecular dynamics simulation of fracture strength and morphology of defective graphene

Different types of defects can be introduced into graphene during material synthesis, and significantly influence the properties of graphene. In this work, we investigated the effects of structural defects, edge functionalisation and reconstruction on the fracture strength and morphology of graphene by molecular dynamics simulations. The minimum energy path analysis was conducted to investigate the formation of Stone-Wales defects. We also employed out-of-plane perturbation and energy minimization principle to study the possi-ble morphology of graphene nanoribbons with edge-termination. Our numerical results show that the fracture strength of graphene is dependent on defects and environmental temperature. However, pre-existing defects may be healed, resulting in strength recovery. Edge functionalization can induce compressive stress and ripples in the edge areas of gra-phene nanoribbons. On the other hand, edge reconstruction contributed to the tensile stress and curved shape in the graphene nanoribbons.