Size effects on tensile and fatigue behaviour of polycrystalline metal foils at the micrometer scale

Tensile and fatigue properties of as-rolled and annealed polycrystalline Cu foils with different thicknesses at the micrometer scale were investigated. Uniaxial tensile testing results showed that with decreasing foil thickness the uniform elongation decreases for both as-rolled and annealed foils, whereas the yield strength and ultimate tensile strength increase for as-rolled foils, but decrease for the annealed foils. For both the as-rolled or annealed foils, bending fatigue resistance decreases with decreasing the foil thickness. Deformation and fatigue damage behaviour of the free-standing foils were characterised as a function of foil thickness. In addition, the fatigue strength of various small-scale Cu foils was compared to understand they physical mechanisms of size effects on mechanical properties of the metallic material at micrometer scales.

Scene invariant crowd counting

This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes. A pre-trained system could therefore be used as a turn-key solution for crowd counting across a wide range of environments. The use of local features allows the proposed algorithm to calculate local occupancy statistics, and Gaussian process regression is used to scale to conditions which are unseen in the training data, also providing confidence intervals for the crowd size estimate. A new crowd counting database is introduced to the computer vision community to enable a wider evaluation over multiple scenes, and the proposed algorithm is tested on seven datasets to demonstrate scene invariance and high accuracy. To the authors' knowledge this is the first system of its kind due to its ability to scale between different scenes and viewpoints.

A study on acoustic emission signal propagation of a small size multi-cylinder diesel engine

Acoustic emission has been found effective in offering earlier fault detection and improving identification capabilities of faults. However, the sensors are inherently uncalibrated. This paper presents a source to sensor paths calibration technique which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time domain, time-frequency domain, and the root mean square (RMS) energy. The results reveal how the RMS energy of a source propagates to the adjacent sensors. The findings lead to allocate the source and estimate its inferences to the adjacent sensor, and finally help to diagnose the small size diesel engines by minimising the crosstalk from multiple cylinders.

What determines real-world meal size? Evidence for pre-meal planning

The customary approach to the study of meal size suggests that ‘events’ occurring during a meal lead to its termination. Recent research, however, suggests that a number of decisions are made before eating commences that may affect meal size. The present study sought to address three key research questions around meal size: the extent to which plate cleaning occurs; prevalence of pre-meal planning and its influence on meal size; and the effect of within-meal experiences, notably the development of satiation. To address these, a large-cohort internet-based questionnaire was developed. Results showed that plate cleaning occurred at 91% of meals, and was planned from the outset in 92% of these cases. A significant relationship between plate cleaning and meal planning was observed. Pre meal plans were resistant to modification over the course of the meal: only 18% of participants reported consumption that deviated from expected. By contrast, 28% reported continuing eating beyond satiation, and 57% stated that they could have eaten more at the end of the meal. Logistic regression confirmed pre-meal planning as the most important predictor of consumption. Together, our findings demonstrate the importance of meal planning as a key determinant of meal size and energy intake.

‘I could eat a horse’! : meal planning determines meal size

Evidence that our food environment can affect meal size is often taken to indicate a failure of ‘conscious control’. By contrast, our research suggests that ‘expected satiation’ (fullness that a food is expected to confer) predicts self-selected meal size. However, the role of meal planning as a determinant of actual meal size remains unresolved, as does the extent to which meal planning is commonplace outside the laboratory. Here, we quantified meal planning and its relation to meal size in a large-cohort study. Participants (N= 764; 25.6 yrs, 78% female) completed a questionnaire containing items relating to their last meal. The majority (91%) of meals were consumed in their entirety. Furthermore, in 92% of these cases the participants decided to consume the whole meal, even before it began. A second major objective was to explore the prospect that meal plans are revised based on within-meal experience (e.g., development of satiation). Only 8% of participants reported ‘unexpected’ satiation that caused them to consume less than anticipated. Moreover, at the end of the meal 57% indicated that they were not fully satiated, and 29% continued eating beyond comfortable satiation (often to avoid wasting food). This pattern was neither moderated by BMI nor dieting status, and was observed across meal types. Together, these data indicate that meals are often planned and that planning corresponds closely with amount consumed. By contrast, we find limited evidence for within-meal modification of these plans, suggesting that ‘pre-meal cognition’ is an important determinant of meal size in humans.

Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

Body composition and appetite : fat-free mass (but not fat mass or BMI) is positively associated with self-determined meal size and daily energy intake in humans

The idea of body weight regulation implies that a biological mechanism exerts control over energy expenditure and food intake. This is a central tenet of energy homeostasis. However, the source and identity of the controlling mechanism have not been identified, although it is often presumed to be some long-acting signal related to body fat, such as leptin. Using a comprehensive experimental platform, we have investigated the relationship between biological and behavioural variables in two separate studies over a 12-week intervention period in obese adults (total n 92). All variables have been measured objectively and with a similar degree of scientific control and precision, including anthropometric factors, body composition, RMR and accumulative energy consumed at individual meals across the whole day. Results showed that meal size and daily energy intake (EI) were significantly correlated with fat-free mass (FFM, P values ,0·02–0·05) but not with fat mass (FM) or BMI (P values 0·11–0·45) (study 1, n 58). In study 2 (n 34), FFM (but not FM or BMI) predicted meal size and daily EI under two distinct dietary conditions (high-fat and low-fat). These data appear to indicate that, under these circumstances, some signal associated with lean mass (but not FM) exerts a determining effect over self-selected food consumption. This signal may be postulated to interact with a separate class of signals generated by FM. This finding may have implications for investigations of the molecular control of food intake and body weight and for the management of obesity.

Unintended consequences of regulatory reporting requirements for small and medium size construction entities : Australian evidence

The Queensland Building Services Authority (QBSA) regulates the construction industry in Queensland, Australia, with licensing requirements creating differential financial reporting obligations, depending on firm size. Economic theories of regulation and behaviour provide a framework for investigating effects of the financial constraints and financial reporting requirements imposed by QBSA licensing. Data are analysed for all small and medium construction entities operating in Queensland between 2001 and 2006. Findings suggesting that construction licensees are categorizing themselves as smaller to avoid the more onerous and costly financial reporting of higher licensee categories are consistent with US findings from the 2002 Sarbanes-Oxley (SOX) regulation which created incentives for small firms to stay small to avoid the costs of compliance with more onerous financial reporting requirements. Such behaviour can have the undesirable economic consequences of adversely affecting employment, investment, wealth creation and financial stability. Insights and implications from the analysed QBSA processes are important for future policy reform and design, and useful to be considered where similar regulatory approaches are planned.

A task-oriented approach to search engine usability studies

Usability is a multi-dimensional characteristic of a computer system. This paper focuses on usability as a measurement of interaction between the user and the system. The research employs a task-oriented approach to evaluate the usability of a meta search engine. This engine encourages and accepts queries of unlimited size expressed in natural language. A variety of conventional metrics developed by academic and industrial research, including ISO standards,, are applied to the information retrieval process consisting of sequential tasks. Tasks range from formulating (long) queries to interpreting and retaining search results. Results of the evaluation and analysis of the operation log indicate that obtaining advanced search engine results can be accomplished simultaneously with enhancing the usability of the interactive process. In conclusion, we discuss implications for interactive information retrieval system design and directions for future usability research. © 2008 Academy Publisher.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Reduced-Size microstrip patch antenna for Bluetooth applications

A novel reduced-size microstrip rectangular patch antenna for Bluetooth operation is presented in this paper. The proposed antenna operates in the 2400 to 2484 MHz ISM Band. Although an air substrate is introduced, antenna occupies a small volume of 33.3×6.6×0.8 mm3. The gain and the impedance bandwidth of the antenna are predicted using a commercial Finite Element Method software package. The predicted results show good agreement with measured data.

Influence of field size on pupil diameter under photopic and mesopic light levels

Purpose: We investigated the interaction between adapting field size and luminance on pupil diameter when cones alone (photopic) or rods and cones (mesopic) were active. Method: Circular achromatic targets (1o to 24o diameter) were presented to eight young participants on a rectangular projector screen. The accommodative influence on pupil diameter was minimized using cycloplegia in the fixing right eye and the consensual pupil reflex was measured in the left eye. Target luminance was adjusted for each stimulus such that corneal flux density (product of field area and luminance) was constant at 3600 cd.deg2m-2 (photopic condition) and 1.49 cd.deg2m-2 (mesopic condition). Results: There were no statistically significant effects of adaptive field size on pupil diameter for either condition. Conclusion: If corneal flux density is kept constant, there will be no change in pupil diameter as the size of the stimulus field increases at either mesopic or photopic lighting levels up to at least 24°.

Separation of acoustic emission signals from small size multi-cylinder diesel engine

This paper presents techniques which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outline, including time-frequency analysis and selection of optimum frequency band.The results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals and the effects of changing parameter values are also outlined. The results on separation of RMS signals show thsi technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events within the combustion process of multi-cylinder diesel engines.

Russian wheat aphids (Diuraphis noxia) in China : native range expansion or recent introduction?

In this study, we explore the population genetics of the Russian wheat aphid (RWA) (Diuraphis noxia), one of the world’s most invasive agricultural pests, in north-western China. We have analysed the data of 10 microsatellite loci and mitochondrial sequences from 27 populations sampled over 2 years in China. The results confirm that the RWAs are holocyclic in China with high genetic diversity indicating widespread sexual reproduction. Distinct differences in microsatellite genetic diversity and distribution revealed clear geographic isolation between RWA populations in northern and southern Xinjiang, China, with gene flow interrupted across extensive desert regions. Despite frequent grain transportation from north to south in this region, little evidence for RWA translocation as a result of human agricultural activities was found. Consequently, frequent gene flow among northern populations most likely resulted from natural dispersal, potentially facilitated by wind currents. We also found evidence for the longterm existence and expansion of RWAs in China, despite local opinion that it is an exotic species only present in China since 1975. Our estimated date of RWA expansion throughout China coincides with the debut of wheat domestication and cultivation practices in western Asia in the Holocene. We conclude that western China represents the limit of the far eastern native range of this species. This study is the most comprehensive molecular genetic investigation of the RWA in its native range undertaken to date and provides valuable insights into the history of the association of this aphid with domesticated cereals and wild grasses.

Role of solids in heavy metals build-up on urban road surfaces

Solids are widely identified as a carrier of harmful pollutants in stormwater runoff exerting a significant risk to receiving waters. This paper outlines the findings of an in-depth investigation on heavy metal adsorption to solids surfaces. Pollutant build-up samples collected from sixteen road sites in residential, industrial and commercial land uses were separated into four particle size ranges and analysed for a range of physico-chemical parameters and nine heavy metals including Iron (Fe), Aluminum (Al), Lead (Pb), Zinc (Zn), Cadmium (Cd), Chromium (Cr), Manganese (Mn), Nickel (Ni) and Copper (Cu). High specific surface area (SSA) and total organic carbon (TOC) content in finer particle size ranges was noted, thus confirming strong correlations with heavy metals. Based on their physico-chemical characteristics, two different types of solids originating from traffic and soil sources were identified. Solids generated by traffic were associated with high loads of heavy metals such as Cd and Cr with strong correlation with SSA. This suggested the existence of surface dependent bonds such as cation exchange between heavy metals and solids. In contrast, Fe, Al and Mn which can be attributed to soil inputs showed strong correlation with TOC suggesting strong bonds such as chemsorption. Zn was found to be primarily attached to solids by bonding with the oxides of Fe, Al and Mn. The data analysis also confirmed the predominance of the finer fraction, with 70% of the solids being finer than 150 µm and containing 60% of the heavy metal pollutant load.