Development of a novel experimental model to investigate the influence of mechanics on bone healing

This dissertation proposed a novel experimental model combining a defect configuration with an active instrumented fixation device to investigate the influence of mechanics on bone healing. The proposed defect configuration aimed to minimise physiological loading within an experimental fracture gap and the instrumented fixator was used for the application of controlled displacements and in vivo stiffness monitoring of the healing process. This thesis has provided a novel approach to advance current knowledge and understanding of mechanobiology, which has been limited in previous experimental models.

Hip power analysis in individuals with transfemoral amputation: A different strategy different from stabilisation during gait stance

Introduction and Objectives Joint moments and joint powers during gait are widely used to determine the effects of rehabilitation programs as well as prosthetic fitting. Following the definition of power (dot product of joint moment and joint angular velocity) it has been previously proposed to analyse the 3D angle between both vectors, αMw. Basically, joint power is maximised when both vectors are parallel and cancelled when both vectors are orthogonal. In other words, αMw < 60° reveals a propulsion configuration (more than 50% of the moment contribute to positive power) while αMw > 120° reveals a resistance configuration (more than 50% of the moment contribute to negative power). A stabilisation configuration (less than 50% of the moment contribute to power) corresponds to 60° < αMw < 120°. Previous studies demonstrated that hip joints of able-bodied adults (AB) are mainly in a stabilisation configuration (αMw about 90°) during the stance phase of gait. [1, 2] Individuals with transfemoral amputation (TFA) need to maximise joint power at the hip while controlling the prosthetic knee during stance. Therefore, we tested the hypothesis that TFAs should adopt a strategy that is different from a continuous stabilisation. The objective of this study was to compute joint power and αMw for TFA and to compare them with AB. Methods Three trials of walking at self-selected speed were analysed for 8 TFAs (7 males and 1 female, 46±10 years old, 1.78±0.08 m 82±13 kg) and 8 ABs (males, 25±3 years old, 1.75±0.04, m 67±6 kg). The joint moments are computed from a motion analysis system (Qualisys, Goteborg, Sweden) and a multi-axial transducer (JR3, Woodland, USA) mounted above the prosthetic knee for TFAs and from a motion analysis system (Motion Analysis, Santa Rosa, USA) and force plates (Bertec, Columbus, USA) for ABs. The TFAs were fitted with an OPRA (Integrum, AB, Gothengurg, Sweden) osseointegrated implant system and their prosthetic designs include pneumatic, hydraulic and microprocessor knees. Previous studies showed that the inverse dynamics computed from the multi-axial transducer is the proper method considering the absorption at the foot and resistance at the knee. Results The peak of positive power at loading response (H1) was earlier and lower for TFA compared to AB. Although the joint power is lower, the 3D angle between joint moment and joint angular velocity, αMw, reveals an obvious propulsion configuration (mean αMw about 20°) for TFA compared to a stabilisation configuration (mean αMw about 70°) for AB. The peaks of negative power at midstance (H2) and of positive power at preswing / initial swing (H3) occurred later, lower and longer for TFA compared to AB. Again, the joint powers are lower for TFA but, in this case, αMw is almost comparable (with a time lag), demonstrating a stabilisation (almost a resistance for TFA, mean αMw about 120°) and a propulsion configuration, respectively. The swing phase is not analysed in the present study. Conclusion The analysis of hip joint power may indicate that TFAs demonstrated less propulsion and resistance than ABs during the stance phase of gait. This is true from a quantitative point of view. On the contrary, the 3D angle between joint moment and joint angular velocity, αMw, reveals that TFAs have a remarkable propulsion strategy at loading response and almost a resistance strategy at midstance while ABs adopted a stabilisation strategy. The propulsion configuration, with αMw close to 0°, seems to aim at maximising the positive joint power. The configuration close to resistance, with αMw far from 180°, might aim at unlocking the prosthetic knee before swing while minimising the negative power. This analysis of both joint power and 3D angle between the joint moment and the joint angular velocity provides complementary insights into the gait strategies of TFA that can be used to support evidence-based rehabilitation and fitting of prosthetic components.

Rate capability of graphite materials as negative electrodes in lithium-ion capacitors

The lithium-ion exchange rate capability of various commercial graphite materials are evaluated using galvanostatic charge/discharge cycling in a half-cell configuration over a wide range of C-rates (0.1 similar to 60C). The results confirm that graphite is capable of de-intercalating stored charge at high rates, but has a poor intercalating rate capability. Decreasing the graphite coating thickness leads to a limited rate performance improvement of the electrode. Reducing the graphite particle size shows enhanced C-rate capability but with increased irreversible capacity loss (ICL). It is demonstrated that the rate of intercalation of lithium-ions into the graphite is significantly limited compared with the corresponding rate of de-intercalation at high C-rates. For the successful utilisation of commercially available conventional graphite as a negative electrode in a lithium-ion capacitor (LIC), its intercalation rate capability needs to be improved or oversized to accommodate high charge rates.

Towards vision-based deep reinforcement learning for robotic motion control

This paper introduces a machine learning based system for controlling a robotic manipulator with visual perception only. The capability to autonomously learn robot controllers solely from raw-pixel images and without any prior knowledge of configuration is shown for the first time. We build upon the success of recent deep reinforcement learning and develop a system for learning target reaching with a three-joint robot manipulator using external visual observation. A Deep Q Network (DQN) was demonstrated to perform target reaching after training in simulation. Transferring the network to real hardware and real observation in a naive approach failed, but experiments show that the network works when replacing camera images with synthetic images.

Nonparametric traversability estimation in partially occluded and deformable terrain

Terrain traversability estimation is a fundamental requirement to ensure the safety of autonomous planetary rovers and their ability to conduct long-term missions. This paper addresses two fundamental challenges for terrain traversability estimation techniques. First, representations of terrain data, which are typically built by the rover’s onboard exteroceptive sensors, are often incomplete due to occlusions and sensor limitations. Second, during terrain traversal, the rover-terrain interaction can cause terrain deformation, which may significantly alter the difficulty of traversal. We propose a novel approach built on Gaussian process (GP) regression to learn, and consequently to predict, the rover’s attitude and chassis configuration on unstructured terrain using terrain geometry information only. First, given incomplete terrain data, we make an initial prediction under the assumption that the terrain is rigid, using a learnt kernel function. Then, we refine this initial estimate to account for the effects of potential terrain deformation, using a near-to-far learning approach based on multitask GP regression. We present an extensive experimental validation of the proposed approach on terrain that is mostly rocky and whose geometry changes as a result of loads from rover traversals. This demonstrates the ability of the proposed approach to accurately predict the rover’s attitude and configuration in partially occluded and deformable terrain.

Protection of a Static Frequency Converter fed traction network, a case study

Aurizon, Australia's largest rail freight operator, is introducing the Static Frequency Converter (SFC) technology into its electric railway network as part of the Bauhinia Electrification Project. The introduction of SFCs has significant implications on the protection systems of the 50kV traction network. The traditional distance protection calculation method does not work in this configuration because of the effect that the SFC in combination with the remote grid has on the apparent impedance, and was substantially reviewed. The standard overcurrent (OC) protection scheme is not suitable due to the minimum fault level being below the maximum load level and was revised to incorporate directionality and under-voltage inhibit. Delta protection was reviewed to improve sensitivity. A new protection function was introduced to prevent back-feeding faults in the transmission network through the grid connection. Protection inter-tripping was included to ensure selectivity between the SFC protection and the system downstream.

Optimal adaptive sequential spatial sampling of soil using pair-copulas

A spatial sampling design that uses pair-copulas is presented that aims to reduce prediction uncertainty by selecting additional sampling locations based on both the spatial configuration of existing locations and the values of the observations at those locations. The novelty of the approach arises in the use of pair-copulas to estimate uncertainty at unsampled locations. Spatial pair-copulas are able to more accurately capture spatial dependence compared to other types of spatial copula models. Additionally, unlike traditional kriging variance, uncertainty estimates from the pair-copula account for influence from measurement values and not just the configuration of observations. This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination. The proposed design methodology is applied to a soil contamination example from the Swiss Jura region. A partial redesign of the original sampling configuration demonstrates the potential of the proposed methodology.

Mathematical modelling and numerical simulation of phosphine flow during grain fumigation in leaky cylindrical silos

The phosphine distribution in a cylindrical silo containing grain is predicted. A three-dimensional mathematical model, which accounts for multicomponent gas phase transport and the sorption of phosphine into the grain kernel is developed. In addition, a simple model is presented to describe the death of insects within the grain as a function of their exposure to phosphine gas. The proposed model is solved using the commercially available computational fluid dynamics (CFD) software, FLUENT, together with our own C code to customize the solver in order to incorporate the models for sorption and insect extinction. Two types of fumigation delivery are studied, namely, fan- forced from the base of the silo and tablet from the top of the silo. An analysis of the predicted phosphine distribution shows that during fan forced fumigation, the position of the leaky area is very important to the development of the gas flow field and the phosphine distribution in the silo. If the leak is in the lower section of the silo, insects that exist near the top of the silo may not be eradicated. However, the position of a leak does not affect phosphine distribution during tablet fumigation. For such fumigation in a typical silo configuration, phosphine concentrations remain low near the base of the silo. Furthermore, we find that half-life pressure test readings are not an indicator of phosphine distribution during tablet fumigation.

On the expressive power of behavioral profiles

Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

Assessing vulnerability at the urban interface

House loss during unplanned bushfires is a complex phenomenon where design, configuration, material and siting, can significantly influence the loss. In collaboration with the Bushfire Cooperative Research Centre the CSIRO has developed a tool to assess the vulnerability of a specific house at the urban interface. The tool is based on a spatial profiling of urban assets including their design, material, surrounding objects and their relationship amongst one another. The analysis incorporates both probabilistic and deterministic parameters, and is based on the impact of radiant heat, flame and embers on the surrounding elements and the structure itself. It provides a breakdown of the attributes and design parameters that contribute to the vulnerability level. This paper describes the tool which allows the user to explore the vulnerability of a house to varying levels of bushfire attacks. The tool is aimed at government agencies interested in building design, town planning and community education for bushfire risk mitigation.

The oxygen migration in the apatite-type lanthanum silicate with the cation substitution

A theoretical model is proposed to determine the effects of Si substitution with Al on the oxygen diffusion in apatite-type lanthanum silicates based on density-functional theory (DFT) calculations for La10(SiO 4)4(AlO4)2O2. Substitution changes the stable configuration for excess oxygen from the split interstitial to a new cluster form with the original cluster. Al doping completely changes the migration mechanism from the interstitialcy one, which was proposed for the La9.33(SiO4)6O2 starting material, to a mechanism which contains an interstitial process. Nevertheless, the migration barrier is calculated to be 0.81 eV, which indicates small changes in oxygen conduction and is consistent with the observations. The present study indicates that the cation substitution on silicon site alone does not promise the improvement of the oxide ion conduction in the lanthanum silicate.

Improved photovoltaic performance of dye-sensitized solar cells with modified self-assembling highly ordered mesoporous TiO 2 photoanodes

Strategies for improving the photovoltaic performance of dye-sensitized solar cells (DSSCs) are proposed by modifying highly transparent and highly ordered multilayer mesoporous TiO 2 photoanodes through nitrogen-doping and top-coating with a light-scattering layer. The mesoporous TiO 2 photoanodes were fabricated by an evaporation-induced self-assembly method. In regard to the modification methods, the light-scattering layer as a top-coating was proved to be superior to nitrogen-doping in enhancing not only the power conversion efficiency but also the fill factor of DSSCs. The optimized bifunctional photoanode consisted of a 30-layer mesoporous TiO 2 thin film (4.15 μm) and a Degussa P25 light-scattering top-layer (4 μm), which gives rise to a ∼200% higher cell efficiency than for unmodified cells and a fill factor of 0.72. These advantages are attributed to its higher dye adsorption, better light scattering, and faster photon-electron transport. Such a photoanode configuration provides an efficient way to enhance the energy conversion efficiency of DSSCs.

Electrochemical properties and intermediate-temperature fuel cell performance of dense yttrium-doped barium zirconate with calcium addition

Although BaZr 0.8Y 0.2O 3-δ(BZY) possesses large bulk proton conductivity and excellent chemical stability, its poor sinterability and grain boundaries block proton conduction. In this work, the effect of Ca as a co-dopant and as a sintering aid (as CaO), on the sinterability, proton conductivity, and fuel cell performance of BZY was investigated. The addition of 4 mol% CaO significantly improved the BZY sinterability: BZY pellets with densities of 92.7% and 97.5% with respect to the theoretical density were obtained after sintering at 1500°C and 1600°C, respectively. The improved BZY sinterability by CaO addition resulted also in a large proton conductivity; at 600°C, the total conductivity of BZY-CaO was 2.14 × 10 -3 S/cm, in wet Ar. Anode-supported fuel cells with 25 μm-thick BZY-CaO electrolyte membranes were fabricated by a dual-layer co-firing technique. The peak power density of the fuel cell with a BZY-Ni/BZY-4CaO/BZY-LSCF (La 0.6Sr 0.4Fe 0.8Co 0.2O 3-δ) configuration was 141 mW/cm 2 at 700°C, several times larger than the reported values of BZY electrolyte membrane fuel cells sintered with the addition of CuO or ZnO, demonstrating promising features for practical fuel cell applications.

Multi-GNSS precise point positioning with raw single-frequency and dual-frequency measurement models

The emergence of multiple satellite navigation systems, including BDS, Galileo, modernized GPS, and GLONASS, brings great opportunities and challenges for precise point positioning (PPP). We study the contributions of various GNSS combinations to PPP performance based on undifferenced or raw observations, in which the signal delays and ionospheric delays must be considered. A priori ionospheric knowledge, such as regional or global corrections, strengthens the estimation of ionospheric delay parameters. The undifferenced models are generally more suitable for single-, dual-, or multi-frequency data processing for single or combined GNSS constellations. Another advantage over ionospheric-free PPP models is that undifferenced models avoid noise amplification by linear combinations. Extensive performance evaluations are conducted with multi-GNSS data sets collected from 105 MGEX stations in July 2014. Dual-frequency PPP results from each single constellation show that the convergence time of undifferenced PPP solution is usually shorter than that of ionospheric-free PPP solutions, while the positioning accuracy of undifferenced PPP shows more improvement for the GLONASS system. In addition, the GLONASS undifferenced PPP results demonstrate performance advantages in high latitude areas, while this impact is less obvious in the GPS/GLONASS combined configuration. The results have also indicated that the BDS GEO satellites have negative impacts on the undifferenced PPP performance given the current “poor” orbit and clock knowledge of GEO satellites. More generally, the multi-GNSS undifferenced PPP results have shown improvements in the convergence time by more than 60 % in both the single- and dual-frequency PPP results, while the positioning accuracy after convergence indicates no significant improvements for the dual-frequency PPP solutions, but an improvement of about 25 % on average for the single-frequency PPP solutions.

System-level analysis of network interfaces for hierarchical MPSoCs

Network Interfaces (NIs) are used in Multiprocessor System-on-Chips (MPSoCs) to connect CPUs to a packet switched Network-on-Chip. In this work we introduce a new NI architecture for our hierarchical CoreVA-MPSoC. The CoreVA-MPSoC targets streaming applications in embedded systems. The main contribution of this paper is a system-level analysis of different NI configurations, considering both software and hardware costs for NoC communication. Different configurations of the NI are compared using a benchmark suite of 10 streaming applications. The best performing NI configuration shows an average speedup of 20 for a CoreVA-MPSoC with 32 CPUs compared to a single CPU. Furthermore, we present physical implementation results using a 28 nm FD-SOI standard cell technology. A hierarchical MPSoC with 8 CPU clusters and 4 CPUs in each cluster running at 800MHz requires an area of 4.56mm2.