Numerical exploration of plastic deformation mechanisms of copper nanowires with surface defects

Based on the molecular dynamics simulation, plastic deformation mechanisms associated with the zigzag stress curves in perfect and surface defected copper nanowires under uniaxial tension are studied. In our previous study, it has found that the surface defect exerts larger influence than the centro-plane defect, and the 45o surface defect appears as the most influential surface defect. Hence, in this paper, the nanowire with a 45o surface defect is chosen to investigate the defect’s effect to the plastic deformation mechanism of nanowires. We find that during the plastic deformation of both perfect and defected nanowires, decrease regions of the stress curve are accompanied with stacking faults generation and migration activities, but during stress increase, the structure of the nanowire appears almost unchanged. We also observe that surface defects have obvious influence on the nanowire’s plastic deformation mechanisms. In particular, only two sets of slip planes are found to be active and twins are also observed in the defected nanowire.

Advanced numerical characterization of mono-crystalline copper with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the mono-crystalline copper with different defects is investigated through tension and nanoindentation simulation. The single-crystal copper nanowire with surface defects is firstly studied through tension. For validation, the tension simulations for nanowire without defect are carried out under different temperatures and strain rates. The defects on nanowires are then systematically studied in considering different defects orientation distribution. It is found that the Young’s modulus is insensitive of surface defects and centro-plane defects. However, the yield strength and yield point show a significant decrease due to the different defects. Specially, the 〖45〗^° defect in surface and in (200) plane exerts the biggest influence to the yield strength, about 34.20% and 51.45% decrease are observed, respectively. Different defects are observed to serve as a dislocation source and different necking positions of the nanowires during tension are found. During nanoindentation simulation, dislocation is found nucleating below the contact area, but no obvious dislocation is generated around the nano-cavity. Comparing with the perfect substrate during nanoindentation, the substrate with nano-cavities emerged less dislocations, it is supposed that the nano-cavity absorbed part of the indent energy, and less plastic deformation happened in the defected substrate.

Numerical exploration of the defect’s effect on mechanical properties of nanowires under torsion

Molecular dynamics (MD) simulations have been carried out to investigate the defect’s effect on the mechanical properties of single-crystal copper nanowire with different surface defects, under torsion deformation. The torsional rigidity is found insensitive to the surface defects and the critical angle appears an obvious decrease due to the surface defects, the largest decrease is found for the nanowire with surface horizon defect. The deformation mechanism appears different degrees of influence due to surface defects. The surface defects play a role of dislocation sources. Comparing with single intrinsic stacking faults formation for the perfect nanowire, much affluent deformation processes have been activated because of surface defects, for instance, we find the twins formation for the nanowire with a surface 45o defect.

Aerial image analysis using spiking neural networks with application to power line corridor monitoring

Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Uncetainty in claiming damages for defects in property

In Project Management Company No 2 Pty Ltd v Cushway Blackford & Associates Pty Ltd [2011] QCA 102 the appellant sought leave to join its parent company party (Project Management Company No 1) as a plaintiff to the proceedings and to amend its statement of claim. It was argued that the parent company had suffered the loss claimed in the proceedings, rather than the appellant. Rule 69(1)(b)(ii) of the Uniform Civil Procedure Rules 1999 (Qld) allows a court at any stage of the proceeding to order that ‘a person whose presence before the court would be desirable, just and convenient to enable the court to adjudicate effectually and completely on all matters in dispute connected with the proceeding’ be include as a party. To determine this issue, the Court of Appeal had to review the law relevant to the proceedings – a claim in negligence for pure economic loss, in particular, the principles espoused by the High Court in Bryan v Maloney(1995) 182 CLR 609 and Woolcock Street Investments Pty Ltd v CDG Pty Ltd (2004) 216 CLR 515.

Biomaterial scaffolds in cartilage-subchondral bone defects influencing the repair of autologous articular cartilage transplants

The repair of articular cartilage typically involves the repair of cartilage-subchondral bone tissue defects. Although various bioactive materials have been used to repair bone defects, how these bioactive materials in subchondral bone defects influence the repair of autologous cartilage transplant remains unclear. The aim of this study was to investigate the effects of different subchondral biomaterial scaffolds on the repair of autologous cartilage transplant in a sheep model. Cylindrical cartilage-subchondral bone defects were created in the right femoral knee joint of each sheep. The subchondral bone defects were implanted with hydroxyapatite-β-tricalcium phosphate (HA-TCP), poly lactic-glycolic acid (PLGA)-HA-TCP dual-layered composite scaffolds (PLGA/HA-TCP scaffolds), or autologous bone chips. The autologous cartilage layer was placed on top of the subchondral materials. After three months, the effect of different subchondral scaffolds on the repair of autologous cartilage transplant was systematically studied by investigating the mechanical strength, structural integration and histological responses. The results showed that the transplanted cartilage layer supported by HA-TCP scaffolds had better structural integration and higher mechanical strength than that supported by PLGA/HA-TCP scaffolds. Furthermore, HA-TCP supported cartilage showed higher expression of acid mucosubstances and glycol-amino-glycan (GAG) contents than that supported by PLGA/HA-TCP scaffolds. Our results suggested that the physicochemical properties, including the inherent mechanical strength and material chemistry of the scaffolds, play important roles in influencing the repair of autologous cartilage transplants. The study may provide useful information for the design and selection of proper subchondral biomaterials to support the repair of both subchondral bone and cartilage defects.

Neural interface systems : a new legal frontier?

In an age where digital innovation knows no boundaries, research in the area of brain-computer interface and other neural interface devices go where none have gone before. The possibilities are endless and as dreams become reality, the implications of these amazing developments should be considered. Some of these new devices have been created to correct or minimise the effects of disease or injury so the paper discusses some of the current research and development in the area, including neuroprosthetics. To assist researchers and academics in identifying some of the legal and ethical issues that might arise as a result of research and development of neural interface devices, using both non-invasive techniques and invasive procedures, the paper discusses a number of recent observations of authors in the field. The issue of enhancing human attributes by incorporating these new devices is also considered. Such enhancement may be regarded as freeing the mind from the constraints of the body, but there are legal and moral issues that researchers and academics would be well advised to contemplate as these new devices are developed and used. While different fact situation surround each of these new devices, and those that are yet to come, consideration of the legal and ethical landscape may assist researchers and academics in dealing effectively with matters that arise in these times of transition. Lawyers could seek to facilitate the resolution of the legal disputes that arise in this area of research and development within the existing judicial and legislative frameworks. Whether these frameworks will suffice, or will need to change in order to enable effective resolution, is a broader question to be explored.

Neural differentiation potential of human bone marrow-derived mesenchymal stromal cells: misleading marker gene expression

Background In contrast to pluripotent embryonic stem cells, adult stem cells have been considered to be multipotent, being somewhat more restricted in their differentiation capacity and only giving rise to cell types related to their tissue of origin. Several studies, however, have reported that bone marrow-derived mesenchymal stromal cells (MSCs) are capable of transdifferentiating to neural cell types, effectively crossing normal lineage restriction boundaries. Such reports have been based on the detection of neural-related proteins by the differentiated MSCs. In order to assess the potential of human adult MSCs to undergo true differentiation to a neural lineage and to determine the degree of homogeneity between donor samples, we have used RT-PCR and immunocytochemistry to investigate the basal expression of a range of neural related mRNAs and proteins in populations of non-differentiated MSCs obtained from 4 donors. Results The expression analysis revealed that several of the commonly used marker genes from other studies like nestin, Enolase2 and microtubule associated protein 1b (MAP1b) are already expressed by undifferentiated human MSCs. Furthermore, mRNA for some of the neural-related transcription factors, e.g. Engrailed-1 and Nurr1 were also strongly expressed. However, several other neural-related mRNAs (e.g. DRD2, enolase2, NFL and MBP) could be identified, but not in all donor samples. Similarly, synaptic vesicle-related mRNA, STX1A could only be detected in 2 of the 4 undifferentiated donor hMSC samples. More significantly, each donor sample revealed a unique expression pattern, demonstrating a significant variation of marker expression. Conclusion The present study highlights the existence of an inter-donor variability of expression of neural-related markers in human MSC samples that has not previously been described. This donor-related heterogeneity might influence the reproducibility of transdifferentiation protocols as well as contributing to the ongoing controversy about differentiation capacities of MSCs. Therefore, further studies need to consider the differences between donor samples prior to any treatment as well as the possibility of harvesting donor cells that may be inappropriate for transplantation strategies.

Human neural cell interactions with orientated electrospun nanofibers in vitro

Aim: Electrospun nanofibers represent potent guidance substrates for nervous tissue repair. Development of nanofiber-based scaffolds for CNS repair requires, as a first step, an understanding of appropriate neural cell type-substrate interactions. Materials & methods: Astrocyte–nanofiber interactions (e.g., adhesion, proliferation, process extension and migration) were studied by comparing human neural progenitor-derived astrocytes (hNP-ACs) and a human astrocytoma cell line (U373) with aligned polycaprolactone (PCL) nanofibers or blended (25% type I collagen/75% PCL) nanofibers. Neuron–nanofiber interactions were assessed using a differentiated human neuroblastoma cell line (SH-SY5Y). Results & discussion: U373 cells and hNP-AC showed similar process alignment and length when associated with PCL or Type I collagen/PCL nanofibers. Cell adhesion and migration by hNP-AC were clearly improved by functionalization of nanofiber surfaces with type I collagen. Functionalized nanofibers had no such effect on U373 cells. Another clear difference between the U373 cells and hNP-AC interactions with the nanofiber substrate was proliferation; the cell line demonstrating strong proliferation, whereas the hNP-AC line showed no proliferation on either type of nanofiber. Long axonal growth (up to 600 µm in length) of SH-SY5Y neurons followed the orientation of both types of nanofibers even though adhesion of the processes to the fibers was poor. Conclusion: The use of cell lines is of only limited predictive value when studying cell–substrate interactions but both morphology and alignment of human astrocytes were affected profoundly by nanofibers. Nanofiber surface functionalization with collagen significantly improved hNP-AC adhesion and migration. Alternative forms of functionalization may be required for optimal axon–nanofiber interactions.

Atomistic exploration of deformation properties of copper nanowires with pre-existing defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, in this paper, the tensile deformation properties of Cu nanowires (NWs) with different pre-existing defects, including single surface defects, surface bi-defects and single internal defects, are systematically studied. In-depth deformation mechanisms of NWs with pre-existing defects are also explored. It is found that Young's modulus is insensitive to different pre-existing defects, but yield strength shows an obvious decrease. Defects are observed influencing greatly on NWs' tensile deformation mechanisms, and playing a role of dislocation sources. Besides of the traditional deformation process dominated by the nucleation and propagation of partial dislocations, the generations of twins, grain boundaries, fivefold deformation twins, hexagonal close-packed (HCP) structure and phase transformation from face-centred cubic (FCC) structure to HCP structure have been triggered by pre-existing defects. It is found that surface defect intends to induce larger influence to yield strength than internal defect. Most importantly, the defect that lies on slip planes exerts larger influence than other defects. As expected, it is also found that the more or longer of the defect, the bigger influence will be induced.

Using strategic movement to calibrate a neural compass : a spiking network for tracking head direction in rats and robots

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that ‘grounding’ of modeled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

Tissue engineering bone - reconstruction of critical sized segmental bone defects in a large animal model

Currently, well established clinical therapeutic approaches for bone reconstruction are restricted to the transplantation of autografts and allografts, and the implantation of metal devices or ceramic-based implants to assist bone regeneration. Bone grafts possess osteoconductive and osteoinductive properties, their application, however, is associated with disadvantages. These include limited access and availability, donor site morbidity and haemorrhage, increased risk of infection, and insufficient transplant integration. As a result, recent research focuses on the development of complementary therapeutic concepts. The field of tissue engineering has emerged as an important alternative approach to bone regeneration. Tissue engineering unites aspects of cellular biology, biomechanical engineering, biomaterial sciences and trauma and orthopaedic surgery. To obtain approval by regulatory bodies for these novel therapeutic concepts the level of therapeutic benefit must be demonstrated rigorously in well characterized, clinically relevant animal models. Therefore, in this PhD project, a reproducible and clinically relevant, ovine, critically sized, high load bearing, tibial defect model was established and characterized as a prerequisite to assess the regenerative potential of a novel treatment concept in vivo involving a medical grade polycaprolactone and tricalciumphosphate based composite scaffold and recombinant human bone morphogenetic proteins.

Quo Vadis? Reliable and Practical Rule Extraction from Neural Networks

Rule extraction from neural network algorithms have been investigated for two decades and there have been significant applications. Despite this level of success, rule extraction from neural network methods are generally not part of data mining tools, and a significant commercial breakthrough may still be some time away. This paper briefly reviews the state-of-the-art and points to some of the obstacles, namely a lack of evaluation techniques in experiments and larger benchmark data sets. A significant new development is the view that rule extraction from neural networks is an interactive process which actively involves the user. This leads to the application of assessment and evaluation techniques from information retrieval which may lead to a range of new methods.