Mechanical behaviour of functionally graded carbon nanofibre/phenolic nanocomposites: numerical modelling and experimental validation

In this study, a finite element-based model was developed to investigate the mechanical behaviour of functionally graded carbon nanofibre (CNF)/phenolic nanocomposites. Four functionally graded nanocomposites (FGNs), a non-graded nanocomposite (NGN), and a pure phenolic with the same geometry and total carbon nanofibre content were designed and fabricated. Flexural tests were conducted to validate the proposed finite element model. Close agreement was obtained between experimental results and numerical predictions. The results showed that flexural modulus can be improved about 45% by controlling the CNF content across the thickness of the samples.

Bending behaviour of step-wise graded carbon nanofiber/polymer nanocomposites

In this study, a finite element-based model was developed to investigate the mechanical behavior of step-wise graded carbon nanofibre/phenolic nanocomposites. Four step-wise graded nanocomposites (FGNs), a non-graded nanocomposite (NGN), and a pure phenolic with the same geometry and total carbon nanofiber content were designed, fabricated and analyzed. Flexural tests were conducted to validate the finite element model. Close agreement was obtained between experimental results and numerical predictions. The results showed that flexural modulus was highly influenced by the compositional gradients.

Vertical movements of North Sea Cod

Various air-breathing marine vertebrates such as seals, turtles and seabirds show distinct patterns of diving behaviour. For fish, the distinction between different vertical behaviours is often less clear-cut, as there are no surface intervals to differentiate between dives. Using data from acoustic tags (n = 23) and archival depth recorders attached to cod Gadus morhua (n = 92) in the southern North Sea, we developed a quantitative method of classifying vertical movements in order to facilitate an objective comparison of the behaviour of different individuals. This method expands the utilisation of data from data storage tags, with the potential for a better understanding of fish behaviour and enhanced individual based behaviour for improved ecosystem modelling. We found that cod were closely associated with the seabed for 90% of the time, although they showed distinct seasonal and spatial patterns in behaviour. For example, cod tagged in the southern North Sea exhibited high rates of vertical movement in spring and autumn that were probably associated with migration, while the vertical movements of resident cod in other areas were much less extensive and were probably related to foraging or spawning behaviours. The full reasons underlying spatial and temporal behavioural plasticity by cod in the North Sea warrant further investigation.

Control of polystyrene batch reactor using fuzzy logic controller

Control of polymerization reactors is a challenging issue for researchers due to the complex reaction mechanisms. A lot of reactions occur simultaneously during polymerization. This leads to a polymerization system that is highly nonlinear in nature. In this work, a nonlinear advanced controller, named fuzzy logic controller (FLC), is developed for monitoring the batch free radical polymerization of polystyrene (PS) reactor. Temperature is used as an intermediate control variable to control polymer quality, because the products quality and quantity of polymer are directly depends on temperature. Different FLCs are developed through changing the number of fuzzy membership functions (MFs) for inputs and output. The final tuned FLC results are compared with the results of another advanced controller, named neural network based model predictive controller (NN-MPC). The simulation results reveal that the FLC performance is better than NN-MPC in terms of quantitative and qualitative performance criterion.

Prediction of pedestrians routes within a built environment in normal conditions

Modelling and prediction of pedestrian routing behaviours within known built environments has recently attracted the attention of researchers across multiple disciplines, owing to the growing demand on urban resources and requirements for efficient use of public facilities. This study presents an investigation into pedestrians' routing behaviours within an indoor environment under normal, non-panic situations. A network-based method using constrained Delaunay triangulation is adopted, and a utility-based model employing dynamic programming is developed. The main contribution of this study is the formulation of an appropriate utility function that allows an effective application of dynamic programming to predict a series of consecutive waypoints within a built environment. The aim is to generate accurate sequence waypoints for the pedestrian walking path using only structural definitions of the environment as defined in a standard CAD format. The simulation results are benchmarked against those from the A* algorithm, and the outcome positively indicates the usefulness of the proposed method in predicting pedestrians' route selection activities. © 2014 Elsevier Ltd. All rights reserved.

Effects of emergence time and early social rearing environment on behaviour of Atlantic salmon: consequences for juvenile fitness and smolt migration

Consistent individual differences in behaviour have been well documented in a variety of animal taxa, but surprisingly little is known about the fitness and life-history consequences of such individual variation. In wild salmonids, the timing of fry emergence from gravel spawning nests has been suggested to be coupled with individual behavioural traits. Here, we further investigate the link between timing of spawning nest emergence and behaviour of Atlantic salmon (Salmo salar), test effects of social rearing environment on behavioural traits in fish with different emergence times, and assess whether behavioural traits measured in the laboratory predict growth, survival, and migration status in the wild. Atlantic salmon fry were sorted with respect to emergence time from artificial spawning nest into three groups: early, intermediate, and late. These emergence groups were hatchery-reared separately or in co-culture for four months to test effects of social rearing environment on behavioural traits. Twenty fish from each of the six treatment groups were then subjected to three individual-based behavioural tests: basal locomotor activity, boldness, and escape response. Following behavioural characterization, the fish were released into a near-natural experimental stream. Results showed differences in escape behaviour between emergence groups in a net restraining test, but the social rearing environment did not affect individual behavioural expression. Emergence time and social environment had no significant effects on survival, growth, and migration status in the stream, although migration propensity was 1.4 to 1.9 times higher for early emerging individuals that were reared separately. In addition, despite individuals showing considerable variation in behaviour across treatment groups, this was not translated into differences in growth, survival, and migration status. Hence, our study adds to the view that fitness (i.e., growth and survival) and life-history predictions from laboratory measures of behaviour should be made with caution and ideally tested in nature.

Board structure and survival of new economy IPO firms

Research Question/Issue: This study examines the relevance of currently accepted best practice recommendations regarding board structure on the survival likelihood of new economy initial public offering companies. We argue that industry context determines governance outcomes. Research Findings/Insights: We study 125 Australian new economy firms listed between 1994 and 2002. Each firm is tracked until the end of 2007 for monitoring their survival. We find that board independence is associated with an increase in the likelihood of corporate survival. We also find that the benefits of board independence increase at a decreasing rate. Theoretical/Academic Implications: The standard best practice recommendation of board independence stems from the monitoring role of directors and is based on agency theory. The results from our study suggest that the recommendation regarding board independence does not work well for new economy firms. While the agency theory based model implies a monotonic relation between board independence and performance, our research suggests that the relationship is nonlinear. This variation occurs because of increased monitoring costs faced by outsiders due to higher information asymmetry and complexity of new economy firms. Our empirical results suggest that inside directors play a complementary role to outsiders in mitigating firm failure. Practitioner/Policy Implications: Our research offers insights to policy makers who are interested in setting best practice standards regarding board structure. Our research suggests that firm/industry characteristics play a crucial role in determining the optimal board structure. In firms/industries where outsiders face significantly higher information processing costs, insiders can play a valuable complementary role to outsiders in enhancing the effectiveness of the board. Thus future hard or soft regulations related to board structure should consider industry context.

Hierarchical dirichlet process for tracking complex topical structure evolution and its application to autism research literature

In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimension. In contrast to previous work our model does not impose a prior on the rate at which documents are added to the corpus nor does it adopt the Markovian assumption which overly restricts the type of changes that the model can capture. Our key technical contribution is a framework based on (i) discretization of time into epochs, (ii) epoch-wise topic discovery using a hierarchical Dirichlet process-based model, and (iii) a temporal similarity graph which allows for the modelling of complex topic changes: emergence and disappearance, evolution, splitting and merging. The power of the proposed framework is demonstrated on the medical literature corpus concerned with the autism spectrum disorder (ASD) - an increasingly important research subject of significant social and healthcare importance. In addition to the collected ASD literature corpus which we made freely available, our contributions also include two free online tools we built as aids to ASD researchers. These can be used for semantically meaningful navigation and searching, as well as knowledge discovery from this large and rapidly growing corpus of literature.

Successional specialization in a reptile community cautions against widespread planned burning and complete fire suppression

Summary: Conservation of biodiversity in fire-prone regions depends on understanding responses to fire in animal communities and the mechanisms governing these responses. We collated data from an Australian semi-arid woodland reptile community (4796 individuals captured over 6 years) to: (i) determine the ability of commonly used shorter-term (2 years) surveys to detect reptile responses to time since fire (TSF) and (ii) investigate whether ecological traits of species reliably predicted their responses to fire. Of 16 reptile species analysed, four had responses to TSF consistent with shorter-term surveys and three showed no response to TSF. Nine species had responses to TSF not detected in previous studies using smaller but substantial subsets of the same data. Among the 13 affected species, times of peak abundance ranged from 1 to 50 years after fire. Nocturnal, burrowing species tended to be early successional and leaf-litter dwellers to be late successional, but these were only weak trends. Synthesis and applications. We found only limited support for a generalizable, trait-based model of succession in reptiles. However, our study revealed that the majority of common reptile species in our study region specialize on a post-fire successional stage and may therefore become threatened if homogeneous fire regimes predominate. Our study highlights the importance of interpreting results from time- or sample-limited fire studies of reptiles with the knowledge that many ecological responses may not have been detected. In such cases, an adaptive or precautionary approach to fire management may be necessary. We found only limited support for a generalizable, trait-based model of succession in reptiles. However, our study revealed that the majority of common reptile species in our study region specialize on a post-fire successional stage and may therefore become threatened if homogeneous fire regimes predominate. Our study highlights the importance of interpreting results from time- or sample-limited fire studies of reptiles with the knowledge that many ecological responses may not have been detected. In such cases, an adaptive or precautionary approach to fire management may be necessary.

Detecting subclinical diabetic cardiac autonomic neuropathy by analyzing ventricular repolarization dynamics

In this study, a linear parametric modeling technique was applied to model ventricular repolarization (VR) dynamics. Three features were selected from the surface ECG recordings to investigate the changes in VR dynamics in healthy and cardiac autonomic neuropathy (CAN) participants with diabetes including heart rate variability (calculated from RR intervals), repolarization variability (calculated from QT intervals), and respiration [calculated by ECG-derived respiration (EDR)]. Surface ECGs were recorded in a supine resting position from 80 age-matched participants (40 with no cardiac autonomic neuropathy (NCAN) and 40 with CAN). In the CAN group, 25 participants had early/subclinical CAN (ECAN) and 15 participants were identified with definite/clinical CAN (DCAN). Detecting subclinical CAN is crucial for designing an effective treatment plan to prevent further cardiovascular complications. For CAN diagnosis, VR dynamics was analyzed using linear parametric autoregressive bivariate (ARXAR) and trivariate (ARXXAR) models, which were estimated using 250 beats of derived QT, RR, and EDR time series extracted from the first 5 min of the recorded ECG signal. Results showed that the EDR-based models gave a significantly higher fitting value (p < 0.0001) than models without EDR, which indicates that QT-RR dynamics is better explained by respiratory-information-based models. Moreover, the QT-RR-EDR model fitting values gradually decreased from the NCAN group to ECAN and DCAN groups, which indicate a decoupling of QT from RR and the respiration signal with the increase in severity of CAN. In this study, only the EDR-based model significantly distinguished ECAN and DCAN groups from the NCAN group (p < 0.05) with large effect sizes (Cohen's d > 0.75) showing the effectiveness of this modeling technique in detecting subclinical CAN. In conclusion, the EDR-based trivariate QT-RR-EDR model was found to be better in detecting the presence and severity of CAN than the bivariate QT-RR model. This finding also establishes the importance of adding respiratory information for analyzing the gradual deterioration of normal VR dynamics in pathological conditions, such as diabetic CAN.

Lung cancer prediction from microarray data by gene expression programming

Lung cancer is a leading cause of cancer-related death worldwide. The early diagnosis of cancer has demonstrated to be greatly helpful for curing the disease effectively. Microarray technology provides a promising approach of exploiting gene profiles for cancer diagnosis. In this study, the authors propose a gene expression programming (GEP)-based model to predict lung cancer from microarray data. The authors use two gene selection methods to extract the significant lung cancer related genes, and accordingly propose different GEP-based prediction models. Prediction performance evaluations and comparisons between the authors' GEP models and three representative machine learning methods, support vector machine, multi-layer perceptron and radial basis function neural network, were conducted thoroughly on real microarray lung cancer datasets. Reliability was assessed by the cross-data set validation. The experimental results show that the GEP model using fewer feature genes outperformed other models in terms of accuracy, sensitivity, specificity and area under the receiver operating characteristic curve. It is concluded that GEP model is a better solution to lung cancer prediction problems.

Sexual segregation in habitat use is smaller than expected in a highly dimorphic marine predator, the southern sea lion

Sexual segregation in habitat use is widely reported in many taxa and can profoundly influence the distribution and behaviour of animals. However, our knowledge of the mechanisms driving sexual segregation is still in its infancy (particularly in marine taxa) and the influence of extrinsic factors in mediating the expression of sex differences in foraging behaviour is underdeveloped. Here, we combine data from biologging tags, with stable isotope analysis of vibrissae, to assess sexual segregation in southern sea lions (SSL) (Otaria flavescens) breeding at the Falkland Islands in the South Atlantic. We found evidence to support segregation, most notably in δ13C and δ15N values. However, in spite of extreme sexual size dimorphism and differing constraints related to female-only parental care, adult male and adult female SSL overlapped considerably in isotopic niches and foraging area, and shared similar foraging trip characteristics (such as distance and duration). This is in contrast to SSL breeding in Argentina, where prior studies report sexual differences in foraging locations and foraging trip characteristics. We posit that sexual segregation in SSL is influenced by habitat availability (defined here as the width of the Patagonian Shelf) and individual foraging preferences, rather than commonly invoked individual-based limiting factors per se.

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.

Solution-focused model for improving individual university teaching

Universities commonly use individual teaching development as one of a suite of strategies to improve teaching and learning outcomes. This paper outlines an individual teaching development programme based on the tenets of solution-focused brief therapy (SFBT). The programme was trialled with a senior lecturer of a large third-year subject in an Australian university. The approach resulted in evidence of positive changes in teaching. The potential and wider application of this approach is considered.