Porous polyurethane coatings bonded onto surface-modified titanium substrates for the growth of an endothelial cell layer

Cardiovascular diseases refer to the class of diseases that involve the heart or blood vessels (arteries and veins). Examples of medical devices for treating the cardiovascular diseases include ventricular assist devices (VADs), artificial heart valves and stents. Metallic biomaterials such as titanium and its alloy are commonly used for ventricular assist devices. However, titanium and its alloy show unacceptable thrombosis, which represents a major obstacle to be overcome. Polyurethane (PU) polymer has better blood compatibility and has been used widely in cardiovascular devices. Thus one aim of the project was to coat a PU polymer onto a titanium substrate by increasing the surface roughness, and surface functionality. Since the endothelium of a blood vessel has the most ideal non-thrombogenic properties, it was the target of this research project to grow an endothelial cell layer as a biological coating based on the tissue engineering strategy. However, seeding endothelial cells on the smooth PU coating surfaces is problematic due to the quick loss of seeded cells which do not adhere to the PU surface. Thus it was another aim of the project to create a porous PU top layer on the dense PU pre-layer-coated titanium substrate. The method of preparing the porous PU layer was based on the solvent casting/particulate leaching (SCPL) modified with centrifugation. Without the step of centrifugation, the distribution of the salt particles was not uniform within the polymer solution, and the degree of interconnection between the salt particles was not well controlled. Using the centrifugal treatment, the pore distribution became uniform and the pore interconnectivity was improved even at a high polymer solution concentration (20%) as the maximal salt weight was added in the polymer solution. The titanium surfaces were modified by alkli and heat treatment, followed by functionlisation using hydrogen peroxide. A silane coupling agent was coated before the application of the dense PU pre-layer and the porous PU top layer. The ability of the porous top layer to grow and retain the endothelial cells was also assessed through cell culture techniques. The bonding strengths of the PU coatings to the modified titanium substrates were measured and related to the surface morphologies. The outcome of the project is that it has laid a foundation to achieve the strategy of endothelialisation for the blood compatibility of medical devices. This thesis is divided into seven chapters. Chapter 2 describes the current state of the art in the field of surface modification in cardiovascular devices such as ventricular assist devices (VADs). It also analyses the pros and cons of the existing coatings, particularly in the context of this research. The surface coatings for VADs have evolved from early organic/ inorganic (passive) coatings, to bioactive coatings (e.g. biomolecules), and to cell-based coatings. Based on the commercial applications and the potential of the coatings, the relevant review is focused on the following six types of coatings: (1) titanium nitride (TiN) coatings, (2) diamond-like carbon (DLC) coatings, (3) 2-methacryloyloxyethyl phosphorylcholine (MPC) polymer coatings, (4) heparin coatings, (5) textured surfaces, and (6) endothelial cell lining. Chapter 3 reviews the polymer scaffolds and one relevant fabrication method. In tissue engineering, the function of a polymeric material is to provide a 3-dimensional architecture (scaffold) which is typically used to accommodate transplanted cells and to guide their growth and the regeneration of tissue. The success of these systems is dependent on the design of the tissue engineering scaffolds. Chapter 4 describes chemical surface treatments for titanium and titanium alloys to increase the bond strength to polymer by altering the substrate surface, for example, by increasing surface roughness or changing surface chemistry. The nature of the surface treatment prior to bonding is found to be a major factor controlling the bonding strength. By increasing surface roughness, an increase in surface area occurs, which allows the adhesive to flow in and around the irregularities on the surface to form a mechanical bond. Changing surface chemistry also results in the formation of a chemical bond. Chapter 5 shows that bond strengths between titanium and polyurethane could be significantly improved by surface treating the titanium prior to bonding. Alkaline heat treatment and H2O2 treatment were applied to change the surface roughness and the surface chemistry of titanium. Surface treatment increases the bond strength by altering the substrate surface in a number of ways, including increasing the surface roughness and changing the surface chemistry. Chapter 6 deals with the characterization of the polyurethane scaffolds, which were fabricated using an enhanced solvent casting/particulate (salt) leaching (SCPL) method developed for preparing three-dimensional porous scaffolds for cardiac tissue engineering. The enhanced method involves the combination of a conventional SCPL method and a step of centrifugation, with the centrifugation being employed to improve the pore uniformity and interconnectivity of the scaffolds. It is shown that the enhanced SCPL method and a collagen coating resulted in a spatially uniform distribution of cells throughout the collagen-coated PU scaffolds.In Chapter 7, the enhanced SCPL method is used to form porous features on the polyurethane-coated titanium substrate. The cavities anchored the endothelial cells to remain on the blood contacting surfaces. It is shown that the surface porosities created by the enhanced SCPL may be useful in forming a stable endothelial layer upon the blood contacting surface. Chapter 8 finally summarises the entire work performed on the fabrication and analysis of the polymer-Ti bonding, the enhanced SCPL method and the PU microporous surface on the metallic substrate. It then outlines the possibilities for future work and research in this area.

Inter- and intra- project knowledge transfer : analysis of knowledge transfer techniques

Many studies in the area of project management and social networks have identified the significance of project knowledge transfer within and between projects. However, only few studies have examined the intra- and inter-projects knowledge transfer activities. Knowledge in projects can be transferred via face-to-face interactions on the one hand, and via IT-based tools on the other. Although companies have allocated many resources to the IT tools, it has been found that they are not always effectively utilised, and people prefer to look for knowledge using social face-to-face interactions. This paper explores how to effectively leverage two alternative knowledge transfer techniques, face-to-face and IT-based tools to facilitate knowledge transfer and enhance knowledge creation for intra- and inter-project knowledge transfer. The paper extends the previous research on the relationships between and within teams by examining the project’s external and internal knowledge networks concurrently. Social network qualitative analysis, using a case study within a small-medium enterprise, was used to examine the knowledge transfer activities within and between projects, and to investigate knowledge transfer techniques. This paper demonstrates the significance of overlapping employees working simultaneously on two or more projects and their impact on facilitating knowledge transfer between projects within a small/medium organisation. This research is also crucial to gaining better understanding of different knowledge transfer techniques used for intra- and inter-project knowledge exchange. The research provides recommendations on how to achieve better knowledge transfer within and between projects in order to fully utilise a project’s knowledge and achieve better project performance.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Magnetic resonance spectroscopy in seizure disorders

Key points • The clinical aims of MR spectroscopy (MRS) in seizure disorders are to help identify, localize and characterize epileptogenic foci. • Lateralizing MRS abnormalities in temporal lobe epilepsy (TLE) may be used clinically in combination with structural and T2 MRI measurements together with other techniques such as EEG, PET and SPECT. • Characteristic metabolite abnormalities are decreased N-acetylaspartate (NAA) with increased choline (Cho) and myoinositol (mI) (short-echo time). • Contralateral metabolite abnormalities are frequently seen in TLE, but are of uncertain significance. • In extra-temporal epilepsy, metabolite abnormalities may be seen where MR imaging (MRI) is normal; but may not be sufficiently localized to be useful clinically. • MRS may help to characterize epileptogenic lesions visible on MRI (aggressive vs. indolent neoplastic, dysplasia). • Spectral editing techniques are required to evaluate specific epilepsy-relevant metabolites (e.g. -aminobutyric acid (GABA)), which may be useful in drug development and evaluation. • MRS with phosphorus (31P) and other nuclei probe metabolism of epilepsy, but are less useful clinically. • There is potential for assessing the of drug mode of action and efficacy through 13C carbon metabolite measurements, while changes in sodium homeostasis resulting from seizure activity may be detected with 23Na MRS.

Combined marrow stromal cell-sheet techniques and high-strength biodegradable composite scaffolds for engineered functional bone grafts

In this study, cell sheets comprising multilayered porcine bone marrow stromal cells (BMSC) were assembled with fully interconnected scaffolds made from medical-grade polycaprolactone–calcium phosphate (mPCL–CaP), for the engineering of structural and functional bone grafts. The BMSC sheets were harvested from culture flasks and wrapped around pre-seeded composite scaffolds. The layered cell sheets integrated well with the scaffold/cell construct and remained viable, with mineralized nodules visible both inside and outside the scaffold for up to 8 weeks culture. Cells within the constructs underwent classical in vitro osteogenic differentiation with the associated elevation of alkaline phosphatase activity and bone-related protein expression. In vivo, two sets of cell-sheet-scaffold/cell constructs were transplanted under the skin of nude rats. The first set of constructs (554mm3) were assembled with BMSC sheets and cultured for 8 weeks before implantation. The second set of constructs (10104mm3) was implanted immediately after assembly with BMSC sheets, with no further in vitro culture. For both groups, neo cortical and well-vascularised cancellous bone were formed within the constructs with up to 40% bone volume. Histological and immunohistochemical examination revealed that neo bone tissue formed from the pool of seeded BMSC and the bone formation followed predominantly an endochondral pathway, with woven bone matrix subsequently maturing into fully mineralized compact bone; exhibiting the histological markers of native bone. These findings demonstrate that large bone tissues similar to native bone can be regenerated utilizing BMSC sheet techniques in conjunction with composite scaffolds whose structures are optimized from a mechanical, nutrient transport and vascularization perspective.

Exploring the needs for SMEs for mobile data technologies : the role of qualitative research techniques

The seemingly exponential nature of technological change provides SMEs with a complex and challenging operational context. The development of infrastructures capable of supporting the wireless application protocol (WAP) and associated 'wireless' applications represents the latest generation of technological innovation with potential appeals to SMEs and end-users alike. This paper aims to understand the mobile data technology needs of SMEs in a regional setting. The research was especially concerned with perceived needs across three market segments : non-adopters, partial-adopters and full-adopters of new technology. The research was exploratory in nature as the phenomenon under scrutiny is relatively new and the uses unclear, thus focus groups were conducted with each of the segments. The paper provides insights for business, industry and academics.

Grafted fluoropolymers as supports for solid-phase organic chemistry : preparation and characterization

Solid-phase organic chemistry has rapidly expanded in the last decade, and, as a consequence, so has the need for the development of supports that can withstand the extreme conditions required to facilitate some reactions. The authors here prepare a thermally stable, grafted fluoropolymer support (see Figure for an example) in three solvents, and found that the penetration of the graft was greatest in dichloromethane.

Chemical functionalities of high and low sulfur Australian coals : a case study using micro attenuated total reflectance–fourier transform infrared (ATR–FTIR) spectrometry

The macerals in bituminous coals with varying organic sulfur content from the Early Permian Greta Coal Measures at three locations (Southland Colliery, Drayton Colliery and the Cranky Corner Basin), in and around the Sydney Basin (Australia), have been studied using light-element electron microprobe (EMP) analysis and micro-ATR–FTIR. Electron microprobe analysis of individual macerals reveals that the vitrinite in both the Cranky Corner Basin and Drayton Colliery (Puxtrees seam) samples have similar carbon contents (ca. 78% C in telocollinite), suggesting that they are of equivalent rank. However, the Cranky Corner coals have anomalously low vitrinite reflectance (down to 0.45%) vs. the Drayton materials (ca. 0.7%). They also have very high organic S content (3–6.5%) and lower O content (ca. 10%) than the equivalent macerals in the Drayton sample (0.7% S and 15.6% O). A study was carried out to investigate the impacts of the high organic S on the functional groups of the macerals in these two otherwise iso-rank, stratigraphically-equivalent seams. An iso-rank low-S coal from the overlying Wittingham Coal Measures near Muswellbrook and coals of slightly higher rank from the Greta Coal Measures at Southland Colliery near Cessnock were also evaluated using the same techniques to extend the data set. Although the telocollinite in the Drayton and Cranky Corner coals have very similar carbon content (ca.78% C), the ATR–FTIR spectra of the vitrinite and inertinite macerals in these respectively low S and high S coals show some distinct differences in IR absorbance from various aliphatic and aromatic functional groups. The differences in absorbance of the aliphatic stretching bands (2800–3000 cm−1) and the aromatic carbon (CC) peak at 1606 cm−1 are very obvious. Compared to that of the Drayton sample (0.7% S and 15% O), the telocollinite of the Cranky Corner coal (6% S and 10% O) clearly shows: (i) less absorbance from OH groups, represented by a broad region around 3553 cm−1, (ii) much stronger aliphatic C–H absorbance (stretching modes around 3000–2800 cm−1 and bending modes around 1442 cm−1) and (iii) less absorbance from aromatic carbon functional groups (peaking at 1606 cm−1). Evaluation of the iso-rank Drayton and Cranky Corner coals shows that: (i) the aliphatic C–H absorbances decrease with increasing oxygen content but increase with increasing organic S content and (ii) the aromatic H to aliphatic H ratio (Har/Hali) for the telocollinite increases with (organic) O%, but decreases progressively with increasing organic S. The high organic S content in the maceral appears to be accompanied by a greater proportion of aliphatic functional groups, possibly as a result of some of the O within maceral ring structures in the high S coal samples being replaced.

Fixing the volatile : studio vocal performance techniques

The process of compiling a studio vocal performance from many takes can often result in the performer producing a new complete performance once this new "best of" assemblage is heard back. This paper investigates the ways that the physical process of recording can alter vocal performance techniques, and in particular, the establishing of a definitive melodic and rhythmic structure. Drawing on his many years of experience as a commercially successful producer, including the attainment of a Grammy award, the author will analyse the process of producing a “credible” vocal performance in depth, with specific case studies and examples. The question of authenticity in rock and pop will also be discussed and, in this context, the uniqueness of the producer’s role as critical arbiter – what gives the producer the authority to make such performance evaluations? Techniques for creating conditions in the studio that are conducive to vocal performances, in many ways a very unnatural performance environment, will be discussed, touching on areas such as the psycho-acoustic properties of headphone mixes, the avoidance of intimidatory practices, and a methodology for inducing the perception of a “familiar” acoustic environment.

Understanding nutrient build-up on urban road surfaces

This paper discusses the outcomes of a research project on nutrients build-up on urban road surfaces. Nutrient build-up was investigated on road sites belonging to residential, industrial and commercial land use. Collected build-up samples were separated into five particle size ranges and were tested for total nitrogen (TN), total phosphorus (TP) and sub species of nutrients, namely, NO2-, NO3-, TKN and PO43-. Multivariate analytical techniques were used to analyse the data and to develop detailed understanding on build-up. Data analysis revealed that the solids loads on urban road surfaces are highly influenced by factors such as land use, antecedent dry period and traffic volume. However, the nutrient build-up process was found to be independent of the type of land use. It was solely dependent on the particle size of solids build-up. Most of the nutrients were associated with the particle size range <150 μm. Therefore, the removal of particles below 150 µm from road surfaces is of importance for the removal of nitrogen and phosphorus from road surface solids build-up. It is also important to consider the differences in the composition of nitrogen and phosphorus build-up in the context of designing effective stormwater quality mitigation strategies.

Development of descriptor tools for the characterization of Australian sugar mill evaporator scale

Cleaning of sugar mill evaporators is an expensive exercise. Identifying the scale components assists in determining which chemical cleaning agents would result in effective evaporator cleaning. The current methods (based on x-ray diffraction techniques, ion exchange/high performance liquid chromatography and thermogravimetry/differential thermal analysis) used for scale characterisation are difficult, time consuming and expensive, and cannot be performed in a conventional analytical laboratory or by mill staff. The present study has examined the use of simple descriptor tests for the characterisation of Australian sugar mill evaporator scales. Scale samples were obtained from seven Australian sugar mill evaporators by mechanical means. The appearance, texture and colour of the scale were noted before the samples were characterised using x-ray fluorescence and x-ray powder diffraction to determine the compounds present. A number of commercial analytical test kits were used to determine the phosphate and calcium contents of scale samples. Dissolution experiments were carried out on the scale samples with selected cleaning agents to provide relevant information about the effect the cleaning agents have on different evaporator scales. Results have shown that by simply identifying the colour and the appearance of the scale, the elemental composition and knowing from which effect the scale originates, a prediction of the scale composition can be made. These descriptors and dissolution experiments on scale samples can be used to provide factory staff with an on-site rapid process to predict the most effective chemicals for chemical cleaning of the evaporators.

Deposition of hydroxyapatite and calcium oxalate dihydrate on a heat exchanger tube

Most studies on the characterisation of deposits on heat exchangers have been based on bulk analysis, neglecting the fine structural features and the compositional profiles of layered deposits. Attempts have been made to fully characterise a fouled stainless steel tube obtained from a quintuple Roberts evaporator of a sugar factory using X-ray diffraction and scanning electron microscopy techniques. The deposit contains three layers at the bottom of the tube and two layers on the other sections and is composed of hydroxyapatite, calcium oxalate dihydrate and an amorphous material. The proportions of these phases varied along the tube height. Energy-dispersive spectroscopy and XRD analysis on the surfaces of the outermost and innermost layers showed that hydroxyapatite was the major phase attached to the tube wall, while calcium oxalate dihydrate (with pits and voids) was the major phase on the juice side. Elemental mapping of the cross-sections of the deposit revealed the presence of a mineral, Si-Mg-Al-Fe-O, which is probably a silicate mineral. Reasons for the defects in the oxalate crystal surfaces, the differences in the crystal size distribution from bottom to the top of the tube and the composite fouling process have been postulated.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Novel analytical and numerical methods for solving fractional dynamical systems

During the past three decades, the subject of fractional calculus (that is, calculus of integrals and derivatives of arbitrary order) has gained considerable popularity and importance, mainly due to its demonstrated applications in numerous diverse and widespread fields in science and engineering. For example, fractional calculus has been successfully applied to problems in system biology, physics, chemistry and biochemistry, hydrology, medicine, and finance. In many cases these new fractional-order models are more adequate than the previously used integer-order models, because fractional derivatives and integrals enable the description of the memory and hereditary properties inherent in various materials and processes that are governed by anomalous diffusion. Hence, there is a growing need to find the solution behaviour of these fractional differential equations. However, the analytic solutions of most fractional differential equations generally cannot be obtained. As a consequence, approximate and numerical techniques are playing an important role in identifying the solution behaviour of such fractional equations and exploring their applications. The main objective of this thesis is to develop new effective numerical methods and supporting analysis, based on the finite difference and finite element methods, for solving time, space and time-space fractional dynamical systems involving fractional derivatives in one and two spatial dimensions. A series of five published papers and one manuscript in preparation will be presented on the solution of the space fractional diffusion equation, space fractional advectiondispersion equation, time and space fractional diffusion equation, time and space fractional Fokker-Planck equation with a linear or non-linear source term, and fractional cable equation involving two time fractional derivatives, respectively. One important contribution of this thesis is the demonstration of how to choose different approximation techniques for different fractional derivatives. Special attention has been paid to the Riesz space fractional derivative, due to its important application in the field of groundwater flow, system biology and finance. We present three numerical methods to approximate the Riesz space fractional derivative, namely the L1/ L2-approximation method, the standard/shifted Gr¨unwald method, and the matrix transform method (MTM). The first two methods are based on the finite difference method, while the MTM allows discretisation in space using either the finite difference or finite element methods. Furthermore, we prove the equivalence of the Riesz fractional derivative and the fractional Laplacian operator under homogeneous Dirichlet boundary conditions – a result that had not previously been established. This result justifies the aforementioned use of the MTM to approximate the Riesz fractional derivative. After spatial discretisation, the time-space fractional partial differential equation is transformed into a system of fractional-in-time differential equations. We then investigate numerical methods to handle time fractional derivatives, be they Caputo type or Riemann-Liouville type. This leads to new methods utilising either finite difference strategies or the Laplace transform method for advancing the solution in time. The stability and convergence of our proposed numerical methods are also investigated. Numerical experiments are carried out in support of our theoretical analysis. We also emphasise that the numerical methods we develop are applicable for many other types of fractional partial differential equations.