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.

Mathematical modelling of tumour growth and interaction with host tissue and the immune system

In this thesis, three mathematical models describing the growth of solid tumour incorporating the host tissue and the immune system response are developed and investigated. The initial model describes the dynamics of the growing tumour and immune response before being extended in the second model by introducing a time-varying dendritic cell-based treatment strategy. Finally, in the third model, we present a mathematical model of a growing tumour using a hybrid cellular automata. These models can provide information to pre-experimental work to assist in designing more effective and efficient laboratory experiments related to tumour growth and interactions with the immune system and immunotherapy.

Damage identification and condition assessment of building structures using frequency response functions and neural networks

This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

The use of artificial neural networks for identifying sustainable biodiesel feedstocks

Over the past few decades, biodiesel produced from oilseed crops and animal fat is receiving much attention as a renewable and sustainable alternative for automobile engine fuels, and particularly petroleum diesel. However, current biodiesel production is heavily dependent on edible oil feedstocks which are unlikely to be sustainable in the longer term due to the rising food prices and the concerns about automobile engine durability. Therefore, there is an urgent need for researchers to identify and develop sustainable biodiesel feedstocks which overcome the disadvantages of current ones. On the other hand, artificial neural network (ANN) modeling has been successfully used in recent years to gain new knowledge in various disciplines. The main goal of this article is to review recent literatures and assess the state of the art on the use of ANN as a modeling tool for future generation biodiesel feedstocks. Biodiesel feedstocks, production processes, chemical compositions, standards, physio-chemical properties and in-use performance are discussed. Limitations of current biodiesel feedstocks over future generation biodiesel feedstock have been identified. The application of ANN in modeling key biodiesel quality parameters and combustion performance in automobile engines is also discussed. This review has determined that ANN modeling has a high potential to contribute to the development of renewable energy systems by accelerating biodiesel research.

Investigation of lymphotoxin α genetic variants in migraine

Migraine is a common neurological disease with a genetic basis affecting approximately 12% of the population. Pain during a migraine attack is associated with activation of the trigeminal nerve system, which carries pain signals from the meninges and the blood vessels infusing the meninges to the trigeminal nucleus in the brain stem. The release of inflammatory mediators following cortical spreading depression (CSD) may further promote and sustain the activation and sensitization of meningeal nociceptors, inducing the persistent throbbing headache characterised in migraine. Lymphotoxin α (LTA) is a cytokine secreted by lymphocytes and is a member of the tumour necrosis factor (TNF) family. Genetic variation with the TNF and LTA genes may contribute to threshold brain excitability, propagation of neuronal hyperexcitability and thus initiation and maintenance of a migraine attack. Three LTA variants rs2009658, rs2844482 and rs2229094 were identified in a recent pGWAS study conducted in the Norfolk Island population as being potentially implicated in migraine with nominally significant p values of p = 0.0093, p = 0.0088 and p = 0.033 respectively. To determine whether these SNPs played a role in migraine in a general outbred population these SNPs were gentoyped in a large case control Australian Caucasian population and tested for association with migraine. All three SNPs showed no association in our cohort (p > 0.05). Validation of GWAS data in independent case-controls cohorts is essential to establish risk validity within specific population groups. The importance of cytokines in modulating neural inflammation and pain threshold in addition to other studies showing associations between TNF-α and SNPs in the LTA gene with migraine, suggests that LTA could be an important factor contributing to migraine. Although the present study did not support a role for the tested LTA variants in migraine, investigation of other variants within the LTA gene is still warranted.

Semaphorin–plexin signalling genes associated with human breast tumourigenesis

Introduction Gene expression profiling has enabled us to demonstrate the heterogeneity of breast cancers. The potential of a tumour to grow and metastasise is partly dependant on its ability to initiate angiogenesis or growth and remodelling of new blood vessels, usually from a pre-existing vascular network, to ensure delivery of oxygen, nutrients, and growth factors to rapidly dividing transformed cells along with access to the systemic circulation. Cell–cell signalling of semaphorin ligands through interaction with their plexin receptors is important for the homeostasis and morphogenesis of many tissues and has been widely studied for a role in neural connectivity, cancer, cell migration and immune responses. This study investigated the role of four semaphorin/plexin signalling genes in human breast cancers in vivo and in vitro. Materials and methods mRNA was extracted from formalin fixed paraffin embedded archival breast invasive ductal carcinoma tissue samples of progressive grades (grades I–III) and compared to tissue from benign tumours. Gene expression profiles were determined by microarray using the Affymetrix GeneChip® Human Genome U133 Plus 2.0 Arrays and validated by Q-PCR using a Corbett RotorGene 6000. Following validation, the gene expression profile of the identified targets was correlated with those of the human breast cancer cell lines MCF-7 and MDA-MD-231. Results The array data revealed that 888 genes were found to be significantly (p ≤ 0.05) differentially expressed between grades I and II tumours and 563 genes between grade III and benign tumours. From these genes, we identified four genes involved in semaphorin–plexin signalling including SEMA4D which has previously been identified as being involved in increased angiogenesis in breast cancers, and three other genes, SEMA4F, PLXNA2 and PLXNA3, which in the literature were associated with tumourigenesis, but not directly in breast tumourigenesis. The microarray analysis revealed that SEMA4D was significantly (P = 0.0347) down-regulated in the grade III tumours compared to benign tumours; SEMA4F, was significantly (P = 0.0159) down-regulated between grades I and II tumours; PLXNA2 was significantly (P = 0.036) down-regulated between grade III and benign tumours and PLXNA3 significantly (P = 0.042) up-regulated between grades I and II tumours. Gene expression of SEMA4D was validated using Q-PCR, demonstrating the same expression profile in both data sets. When the sample set was increased to incorporate more cases, SEMA4D continued to follow the same expression profile, including statistical significance for the differences observed and small standard deviations. In vitro the same pattern was present where expression for SEMA4D was significantly higher in MDA-MB-231 cells when compared to MCF-7 cells. The expression of SEMA4F, PLXNA2 and PLXNA3 could not be validated using Q-PCR, however in vitro analysis of these three genes revealed that both SEMA4F and PLXNA3 followed the microarray trend in expression, although they did not reach significance. In contrast, PLXNA2 demonstrated statistical significance and was in concordance with the literature. Discussion We, and others, have proposed SEMA4D to be a gene with a potentially protective effect in benign tumours that contributes to tumour growth and metastatic suppression. Previous data supports a role for SEMA4F as a tumour suppressor in the peripheral nervous system but our data seems to indicate that the gene is involved in tumour progression in breast cancer. Our in vitro analysis of PLXNA2 revealed that the gene has higher expression in more aggressive breast cancer cell types. Finally, our in vitro analysis on PLXNA3 also suggest that this gene may have some form of growth suppressive role in breast cancer, in addition to a similar role for the gene previously reported in ovarian cancer. From the data obtained in this study, SEMA4D may have a role in more aggressive and potentially metastatic breast tumours. Conclusions Semaphorins and their receptors, the plexins, have been implicated in numerous aspects of neural development, however their expression in many other epithelial tissues suggests that the semaphorin–plexin signalling system also contributes to blood vessel growth and development. These findings warrant further investigation of the role of semaphorins and plexins and their role in normal and tumour-induced angiogenesis in vivo and in vitro. This may represent a new front of attack in anti-angiogenic therapies of breast and other cancers.

Heparan sulfate proteoglycans, tumour progression and the cancer stem cell niche

The cancer stem cell hypothesis states that tumours arise from cells with the ability to self-renew and differentiate into multiple cell types, and that these cells persist in tumors as a distinct population that can cause disease relapse and hence metastasis. The crux of this hypothesis is that these cells are the only cells capable of, by themselves, giving rise to new tumours. What proportion of a tumour consists of these stem cells, where are they localised, how are they regulated, and how can we identify them? The stromal cells embedded within the extracellular matrix (ECM) not only provide a scaffold but also produce ECM constituents for use by stem cells. Heparan sulfate proteoglycans (HSPGs) are ubiquitous to this cell niche and interact with a large number of ligands including growth factors, their receptors, and ECM structural components. It is still unclear whether ECM degradation and subsequent metastasis is a result of proteases produced by the tumour cells themselves or by cells within the stromal compartment. The identification of the cellular origin of cancer stem cells along with microenvironmental changes involved in the initiation, progression and the malignant conversion of all cancers is critical to the development of targeted therapeutics. As ubiquitous members of the ECM microenvironment and hence the cancer cell niche, HSPGs are candidates for a central role in these processes.

An assessment of MMP and TIMP gene expression in cell lines and stroma : tumour differences in microdissected breast cancer biopsies

To examine matrix metalloproteinase (MMP) and tissue inhibitor of metalloproteinases (TIMP) mRNA levels in archival breast cancer biopsies, we employed microdissection to separate tumour tissue from the surrounding breast tissue, or stroma and RT-PCR to determine gross qualitative and small quantitative differences in the patterns of expression. In this study, a significant correlation (p < 0.05, by Mann-Whitney U analysis) between TIMP-2 expression and lymph node involvement was identified, while MMP-11 and TIMP-1 expression patterning also significantly (p < 0.05) differed between those tumours showing calcification and those that did not. When compared by Spearmans’ ρ correlation analysis, a significant association (p < 0.05, ρ = 0.404) was identified in the pattern of MMP-2 and MMP-9 gene expression. In this study, the use of microdissection and a systematic strategy of RT-PCR analysis have allowed us to investigate localized MMP and MMP inhibitor expression within breast tumours. We have identified patterns of gene expression that may further reveal aspects of breast carcinogenesis, and a robust method for examining changes in clinically important genes using archival biopsies and across stroma-tumour boundaries.

18FDG uptake during induction chemoradiation for oesophageal cancer fails to predict histomorphological tumour response

To determine whether [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) could predict the pathological response in oesophageal cancer after only the first week of neoadjuvant chemoradiation. Thirty-two patients with localised oesophageal cancer had a pretreatment PET scan and a repeat after the first week of chemoradiation. The change in mean maximum standardised uptake value (SUV) and volume of metabolically active tissue (MTV) was compared with the tumour regression grade (TRG) in the final histology. Those who achieved a TRG of 1 and 2 were deemed responders and 3-5 nonresponders. In the responders (28%), the SUV fell from 12.6 (±6.3) to 8.1 (±2.9) after 1 week of chemoradiation (P = 0.070). In nonresponders (72%), the results were 9.7 (±5.4) and 7.1 (±3.8), respectively (P = 0.003). The MTV in responders fell from 36.6 (±22.7) to 22.3 (±10.4) cm3 (P = 0.180), while in nonresponders, this fell from 35.9 (±36.7) to 31.9 (±52.7) cm3 (P = 0.405). There were no significant differences between responders and nonresponders. The hypothesis that early repeat FDG-PET scanning may predict histomorphologic response was not proven. This may reflect an inflammatory effect of radiation that obscures tumour-specific metabolic changes at this time. This assessment may have limited application in predicting response to multimodal regimens for oesophageal cancer. © 2006 Cancer Research UK.

Potential role of bcl-2 as a suppressor of tumour angiogenesis in non- small-cell lung cancer

It has been reported that genes regulating apoptosis may play a role in tumoral angiogenesis. This study examined the relationship between tumour vascularization, a measure of tumour angiogenesis, and bcl-2 and p53 expression in operable non-small-cell lung cancer (NSCLC). The relationship between bcl-2, p53 and tumour vascularization and epidermal-growth-factor- receptor(EGFR) and c-erbB-2 expression was also studied. Tissue sections from resected tumour specimens of 107 NSCLC patients were evaluated immunohistochemically for vascular grade and bcl-2, p53, EGFR and c-erbB-2 expression. bcl-2 expression was found in 20/107 (19%) cases and was associated with squamous-cell histology (p = 0.03). A strong inverse relationship was found between bcl-2 expression and vascular grade (p = 0.005). All c-erbB-2-positive cases were negative for bcl-2 expression (p = 0.01). Overall no association was found between c-erbB-2 expression and vascular grade. However, in bcl-2-negative cases positive c-erbB-2 expression correlated with low angiogenesis (p = 0.05). No relationship was found between p53 and EGFR expression and bcl-2, c-erbB-2 or vascular grade. The improved prognosis reported in bcl-2-positive NSCLC may be related to low tumour vascularization. The results suggest that the anti-apoptotic gene bcl- 2 plays a role in regulating tumour angiogenesis. Since normal lung epithelium expresses bcl-2, a sequence of tumour progression involving loss of bcl-2, then activation of c-erbB-2 or increase in tumour vascularization is proposed.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

Tumour necrosis is an independent prognostic marker in non-small cell lung cancer : correlation with biological variables

Background Tumour necrosis (TN) is recognized to be a consequence of chronic cellular hypoxia. TN and hypoxia correlate with poor prognosis in solid tumours. Methods In a retrospective study the prognostic implications of the extent of TN was evaluated in non-small cell lung cancer (NSCLC) and correlated with clinicopathological variables and expression of epidermal growth factor receptor, Bcl-2, p53 and matrix metalloproteinase-9 (MMP-9). Tissue specimens from 178 surgically resected cases of stage I-IIIA NSCLC with curative intent were studied. The specimens were routinely processed, formalin-fixed and paraffin-embedded. TN was graded as extensive or either limited or absent by two independent observers; disagreements were resolved using a double-headed microscope. The degree of reproducibility was estimated by re-interpreting 40 randomly selected cases after a 4 month interval. Results Reproducibility was attained in 36/40 cases, Kappa score=0.8 P<0.001. TN correlated with T-stage (P=0.001), platelet count (P=0.004) and p53 expression (P=0.031). Near significant associations of TN with N-stage (P=0.063) and MMP-9 expression (P=0.058) were seen. No association was found with angiogenesis (P=0.98). On univariate (P=0.0016) and multivariate analysis (P=0.023) TN was prognostic. Conclusion These results indicate that extensive TN reflects an aggressive tumour phenotype in NSCLC and may improve the predictive power of the TMN staging system. The lack of association between TN and angiogenesis may be important although these variables were not evaluated on serial sections. © 2002 Elsevier Science Ireland Ltd. All rights reserved.

Existence of travelling wave solutions for a model of tumour invasion

The existence of travelling wave solutions to a haptotaxis dominated model is analysed. A version of this model has been derived in Perumpanani et al. (1999) to describe tumour invasion, where diffusion is neglected as it is assumed to play only a small role in the cell migration. By instead allowing diffusion to be small, we reformulate the model as a singular perturbation problem, which can then be analysed using geometric singular perturbation theory. We prove the existence of three types of physically realistic travelling wave solutions in the case of small diffusion. These solutions reduce to the no diffusion solutions in the singular limit as diffusion as is taken to zero. A fourth travelling wave solution is also shown to exist, but that is physically unrealistic as it has a component with negative cell population. The numerical stability, in particular the wavespeed of the travelling wave solutions is also discussed.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Crucial roles for olfactory ensheathing cells and olfactory mucosal cells in the repair of damaged neural tracts

Olfactory ensheathing cells, the glial cells of the olfactory nervous system, exhibit unique growth-promoting and migratory properties that make them interesting candidates for cell therapies targeting neuronal injuries such as spinal cord injury. Transplantation of olfactory cells is feasible and safe in humans; however, functional outcomes are highly variable with some studies showing dramatic improvements and some no improvements at all. We propose that the reason for this is that the identity and purity of the cells is different in each individual study. We have shown that olfactory ensheathing cells are not a uniform cell population and that individual subpopulations of OECs are present in different regions of the olfactory nervous system, with strikingly different behaviors. Furthermore, the presence of fibroblasts and other cell types in the transplant can dramatically alter the behavior of the transplanted glial cells. Thus, a thorough characterization of the differences between olfactory ensheathing cell subpopulations and how the behavior of these cells is affected by the presence of other cell types is highly warranted.