Measurements of particle emissions from nanotechnology processes, with assessment of measuring techniques and workplace controls

The overall aim of this project was to contribute to existing knowledge regarding methods for measuring characteristics of airborne nanoparticles and controlling occupational exposure to airborne nanoparticles, and to gather data on nanoparticle emission and transport in various workplaces. The scope of this study involved investigating the characteristics and behaviour of particles arising from the operation of six nanotechnology processes, subdivided into nine processes for measurement purposes. It did not include the toxicological evaluation of the aerosol and therefore, no direct conclusion was made regarding the health effects of exposure to these particles. Our research included real-time measurement of sub, and supermicrometre particle number and mass concentration, count median diameter, and alveolar deposited surface area using condensation particle counters, an optical particle counter, DustTrak photometer, scanning mobility particle sizer, and nanoparticle surface area monitor, respectively. Off-line particle analysis included scanning and transmission electron microscopy, energy-dispersive x-ray spectrometry, and thermal optical analysis of elemental carbon. Sources of fibrous and non-fibrous particles were included.

Variability, regularity and coupling measures distinguish PD tremor from voluntary 5Hz tremor

A characteristic of Parkinson's disease (PD) is the development of tremor within the 4–6 Hz range. One method used to better understand pathological tremor is to compare the responses to tremor-type actions generated intentionally in healthy adults. This study was designed to investigate the similarities and differences between voluntarily generated 4–6 Hz tremor and PD tremor in regards to their amplitude, frequency and coupling characteristics. Tremor responses for 8 PD individuals (on- and off-medication) and 12 healthy adults were assessed under postural and resting conditions. Results showed that the voluntary and PD tremor were essentially identical with regards to the amplitude and peak frequency. However, differences between the groups were found for the variability (SD of peak frequency, proportional power) and regularity (Approximate Entropy, ApEn) of the tremor signal. Additionally, coherence analysis revealed strong inter-limb coupling during voluntary conditions while no bilateral coupling was seen for the PD persons. Overall, healthy participants were able to produce a 5 Hz tremulous motion indistinguishable to that of PD patients in terms of peak frequency and amplitude. However, differences in the structure of variability and level of inter-limb coupling were found for the tremor responses of the PD and healthy adults. These differences were preserved irrespective of the medication state of the PD persons. The results illustrate the importance of assessing the pattern of signal structure/variability to discriminate between different tremor forms, especially where no differences emerge in standard measures of mean amplitude as traditionally defined.

Frame-rate stereopsis using non-parametric transforms and programmable logic

A frame-rate stereo vision system, based on non-parametric matching metrics, is described. Traditional metrics, such as normalized cross-correlation, are expensive in terms of logic. Non-parametric measures require only simple, parallelizable, functions such as comparators, counters and exclusive-or, and are thus very well suited to implementation in reprogrammable logic.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Approaches to designing for older adults' intuitive interaction with complex devices

Many older people have difficulties using modern consumer products due to increased product complexity both in terms of functionality and interface design. Previous research has shown that older people have more difficulty in using complex devices intuitively when compared to the younger. Furthermore, increased life expectancy and a falling birth rate have been catalysts for changes in world demographics over the past two decades. This trend also suggests a proportional increase of older people in the work-force. This realisation has led to research on the effective use of technology by older populations in an effort to engage them more productively and to assist them in leading independent lives. Ironically, not enough attention has been paid to the development of interaction design strategies that would actually enable older users to better exploit new technologies. Previous research suggests that if products are designed to reflect people's prior knowledge, they will appear intuitive to use. Since intuitive interfaces utilise domain-specific prior knowledge of users, they require minimal learning for effective interaction. However, older people are very diverse in their capabilities and domain-specific prior knowledge. In addition, ageing also slows down the process of acquiring new knowledge. Keeping these suggestions and limitations in view, the aim of this study was set to investigate possible approaches to developing interfaces that facilitate their intuitive use by older people. In this quest to develop intuitive interfaces for older people, two experiments were conducted that systematically investigated redundancy (the use of both text and icons) in interface design, complexity of interface structure (nested versus flat), and personal user factors such as cognitive abilities, perceived self-efficacy and technology anxiety. All of these factors could interfere with intuitive use. The results from the first experiment suggest that, contrary to what was hypothesised, older people (65+ years) completed the tasks on the text only based interface design faster than on the redundant interface design. The outcome of the second experiment showed that, as expected, older people took more time on a nested interface. However, they did not make significantly more errors compared with younger age groups. Contrary to what was expected, older age groups also did better under anxious conditions. The findings of this study also suggest that older age groups are more heterogeneous in their capabilities and their intuitive use of contemporary technological devices is mediated more by domain-specific technology prior knowledge and by their cognitive abilities, than chronological age. This makes it extremely difficult to develop product interfaces that are entirely intuitive to use. However, by keeping in view the cognitive limitations of older people when interfaces are developed, and using simple text-based interfaces with flat interface structure, would help them intuitively learn and use complex technological products successfully during early encounter with a product. These findings indicate that it might be more pragmatic if interfaces are designed for intuitive learning rather than for intuitive use. Based on this research and the existing literature, a model for adaptable interface design as a strategy for developing intuitively learnable product interfaces was proposed. An adaptable interface can initially use a simple text only interface to help older users to learn and successfully use the new system. Over time, this can be progressively changed to a symbols-based nested interface for more efficient and intuitive use.

Comparison of two suspension control strategies for multi-axle heavy truck

Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver’s seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.

Assessing the potential of mathematics textbooks to promote deep learning

Curriculum documents for mathematics emphasise the importance of promoting depth of knowledge rather than shallow coverage of the curriculum. In this paper, we report on a study that explored the analysis of junior secondary mathematics textbooks to assess their potential to assist in teaching and learning aimed at building and applying deep mathematical knowledge. The method of analysis involved the establishment of a set of specific curriculum goals and associated indicators, based on research into the teaching and learning of a particular field within the mathematics curriculum, namely proportion and proportional reasoning. Topic selection was due to its pervasive nature throughout the school mathematics curriculum at this level. As a result of this study, it was found that the five textbook series examined provided limited support for the development of multiplicative structures required for proportional reasoning, and hence would not serve well the development of deep learning of mathematics. The study demonstrated a method that could be applied to the analysis of junior secondary mathematics in many parts of the world.

Load bearing improves the limits of agreement for repeated in vivo measures of the speed of sound in human Achilles tendon

Axial acoustic wave propagation has been widely used in evaluating the mechanical properties of human bone in vivo. However, application of this technique to monitor soft tissues, such as tendon, has received comparatively little scientific attention. Laboratory-based research has established that axial acoustic wave transmission is not only related to the physical properties of equine tendon but is also proportional to tensile load to which it is exposed (Miles et al., 1996; Pourcelot et al., 2005). The reproducibility of the technique for in vivo measurements in human tendon, however, has not been established. The aim of this study was to evaluate the limits of agreement for repeated measures of the speed of sound (SoS) in human Achilles tendon in vivo. Methods: A custom built ultrasound device, consisting of an A-mode 1MHz emitter and two regularly spaced receivers, was used to measure the SoS in the mid-portion of the Achilles tendon in ten healthy males and ten females (mean age: 33.8 years, range 23-56 yrs; height: 1.73±0.08 m; weight: 68.4±15.3 kg). The emitter and receivers were held at fixed positions by a polyethylene frame and maintained in close contact with the skin overlying the tendon by means of elasticated straps. Repeated SoS measurements were taken with the subject prone (non-weightbearing and relaxed Achilles tendon) and during quiet bipedal and unipedal stance. In each instance, the device was detached and repositioned prior to measurement. Results: Limits of agreement for repeated SoS measures during non-weightbearing and bipedal and unipedal stance were ±53, ±28 and ±21 m/s, respectively. The average SoS in the non-weightbearing Achilles tendon was 1804±198 m/s. There was a significant increase in the average SoS during bilateral (2122±135 m/s) (P < 0.05) and unilateral (2221±79 m/s) stance (P < 0.05). Conclusions: Repeated SoS measures in human Achilles tendon were more reliable during stance than under non-weightbearing conditions. These findings are consistent with previous research in equine tendon in which lower variability in SoS was observed with increasing tensile load (Crevier-Denoix et al, 2009). Since the limits of agreement for Achilles tendon SoS are nearly 5% of the changes previously observed during walking and therapeutic heel raise exercises, acoustic wave transmission provides a promising new non-invasive method for determining tendon properties during sports and rehabilitation related activities.

A Flight control scheme to improve position tracking performance of rotary-wing UASs

This paper outlines an innovative and feasible flight control scheme for a rotary-wing unmanned aerial system (RUAS) with guaranteed safety and reliable flight quality in a gusty environment. The proposed control methodology aims to increase gust-attenuation capability of a RUAS to ensure improved flight performance when strong gusts occur. Based on the design of an effective estimator, an altitude controller is firstly constructed to synchronously compensate for fluctuations of the main rotor thrust which might lead to crashes in a gusty environment. Afterwards, a nonlinear state feedback controller is proposed to stabilize horizontal positions of the RUAS with gust-attenuation property. Performance of the proposed control framework is evaluated using parameters of a Vario XLC helicopter and high-fidelity simulations show that the proposed controllers can effectively reduce side-effect of gusts and demonstrate performance improvement when compared with the proportional-integral-derivative (PID) controllers.

A neural-network based flight controller for UASs

This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

Children exposure assessment to ultrafine particles and black carbon: The role of transport and cooking activities

An accurate evaluation of the airborne particle dose-response relationship requires detailed measurements of the actual particle concentration levels that people are exposed to, in every microenvironment in which they reside. The aim of this work was to perform an exposure assessment of children in relation to two different aerosol species: ultrafine particles (UFPs) and black carbon (BC). To this purpose, personal exposure measurements, in terms of UFP and BC concentrations, were performed on 103 children aged 8-11 years (10.1 ± 1.1 years) using hand-held particle counters and aethalometers. Simultaneously, a time-activity diary and a portable GPS were used to determine the children’s daily time-activity pattern and estimate their inhaled dose of UFPs and BC. The median concentration to which the study population was exposed was found to be comparable to the high levels typically detected in urban traffic microenvironments, in terms of both particle number (2.2×104 part. cm-3) and BC (3.8 μg m-3) concentrations. Daily inhaled doses were also found to be relatively high and were equal to 3.35×1011 part. day-1 and 3.92×101 μg day-1 for UFPs and BC, respectively. Cooking and using transportation were recognized as the main activities contributing to overall daily exposure, when normalized according to their corresponding time contribution for UFPs and BC, respectively. Therefore, UFPs and BC could represent tracers of children exposure to particulate pollution from indoor cooking activities and transportation microenvironments, respectively.

Familial recurrence risks for multiple sclerosis in Australia

BACKGROUND: Genetic susceptibility to multiple sclerosis (MS) has been recognised for many years. Considerable data exist from the northern hemisphere regarding the familial recurrence risks for MS, but there are few data for the southern hemisphere and regions at lower latitude such as Australia. To investigate the interaction between environmental and genetic causative factors in MS, the authors undertook a familial recurrence risk study in three latitudinally distinct regions of Australia. METHODS: Immediate and extended family pedigrees have been collected for three cohorts of people with MS in Queensland, Victoria and Tasmania spanning 15° of latitude. Age of onset data from Queensland were utilised to estimate age-adjusted recurrence rates. RESULTS: Recurrence risks in Australia were significantly lower than in studies from northern hemisphere populations. The age-adjusted risk for siblings across Australia was 2.13% compared with 3.5% for the northern hemisphere. A similar pattern was seen for other relatives. The risks to relatives were proportional to the population risks for each site, and hence the sibling recurrence-risk ratio (λ(s)) was similar across all sites. DISCUSSION: The familial recurrence risk of MS in Australia is lower than in previously reported studies. This is directly related to the lower population prevalence of MS. The overall genetic susceptibility in Australia as measured by the λ(s) is similar to the northern hemisphere, suggesting that the difference in population risk is explained largely by environmental factors rather than by genetic admixture.

The influence of oxygenated organic aerosols (OOA) on the oxidative potential of diesel and biodiesel particulate matter

Generally, the magnitude of pollutant emissions from diesel engines running on biodiesel fuel is ultimately coupled to the structure of respective molecules that constitutes the fuel. Previous studies demonstrated the relationship between organic fraction of PM and its oxidative potential. Herein, emissions from a diesel engine running on different biofuels were analysed in more detail to explore the role different organic fractions play in the measured oxidative potential. In this work, a more detailed chemical analysis of biofuel PM was undertaken using a compact Time of Flight Aerosol Mass Spectrometer (c-ToF AMS). This enabled a better identification of the different organic fractions that contribute to the overall measured oxidative potentials. The concentration of reactive oxygen species (ROS) was measured using a profluorescent nitroxide molecular probe 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-(phenylethynyl)anthracene (BPEAnit). Therefore the oxidative potential of the PM, measured through the ROS content, although proportional to the total organic content in certain cases shows a much higher correlation with the oxygenated organic fraction as measured by the c-ToF AMS. This highlights the importance of knowing the surface chemistry of particles for assessing their health impacts. It also sheds light onto new aspects of particulate emissions that should be taken into account when establishing relevant metrics for assessing health implications of replacing diesel with alternative fuels.

Improving the PLDA based speaker verification in limited microphone data conditions

A significant amount of speech data is required to develop a robust speaker verification system, but it is difficult to find enough development speech to match all expected conditions. In this paper we introduce a new approach to Gaussian probabilistic linear discriminant analysis (GPLDA) to estimate reliable model parameters as a linearly weighted model taking more input from the large volume of available telephone data and smaller proportional input from limited microphone data. In comparison to a traditional pooled training approach, where the GPLDA model is trained over both telephone and microphone speech, this linear-weighted GPLDA approach is shown to provide better EER and DCF performance in microphone and mixed conditions in both the NIST 2008 and NIST 2010 evaluation corpora. Based upon these results, we believe that linear-weighted GPLDA will provide a better approach than pooled GPLDA, allowing for the further improvement of GPLDA speaker verification in conditions with limited development data.