The effect of sample and sample matrix on DNA processing: Mechanisms for the detection and management of inhibition in forensic samples

The presence of inhibitory substances in biological forensic samples has, and continues to affect the quality of the data generated following DNA typing processes. Although the chemistries used during the procedures have been enhanced to mitigate the effects of these deleterious compounds, some challenges remain. Inhibitors can be components of the samples, the substrate where samples were deposited or chemical(s) associated to the DNA purification step. Therefore, a thorough understanding of the extraction processes and their ability to handle the various types of inhibitory substances can help define the best analytical processing for any given sample. A series of experiments were conducted to establish the inhibition tolerance of quantification and amplification kits using common inhibitory substances in order to determine if current laboratory practices are optimal for identifying potential problems associated with inhibition. DART mass spectrometry was used to determine the amount of inhibitor carryover after sample purification, its correlation to the initial inhibitor input in the sample and the overall effect in the results. Finally, a novel alternative at gathering investigative leads from samples that would otherwise be ineffective for DNA typing due to the large amounts of inhibitory substances and/or environmental degradation was tested. This included generating data associated with microbial peak signatures to identify locations of clandestine human graves. Results demonstrate that the current methods for assessing inhibition are not necessarily accurate, as samples that appear inhibited in the quantification process can yield full DNA profiles, while those that do not indicate inhibition may suffer from lowered amplification efficiency or PCR artifacts. The extraction methods tested were able to remove >90% of the inhibitors from all samples with the exception of phenol, which was present in variable amounts whenever the organic extraction approach was utilized. Although the results attained suggested that most inhibitors produce minimal effect on downstream applications, analysts should practice caution when selecting the best extraction method for particular samples, as casework DNA samples are often present in small quantities and can contain an overwhelming amount of inhibitory substances.^

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

An Islanding Detection Method based on Impedance Estimation and Grid Identification for Grid-Tie Distributed Power Generation Systems

Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.

The role of cancer related inflammation, Src family kinases and matrix metalloproteinase 9 in colorectal cancer

Colorectal cancer (CRC) is the third most common cancer in the UK with 41,000 new cases diagnosed in 2011. Despite undergoing potentially curative resection, a significant amount of patients develop recurrence. Biomarkers that aid prognostication or identify patients who are suitable for adjuvant treatments are needed. The TNM staging system does a reasonably good job at offering prognostic information to the treating clinician, but it could be better and identifying methods of improving its accuracy are needed. Tumour progression is based on a complex relationship between tumour behaviour and the hosts’ inflammatory responses. Sustained tumour cell proliferation, evading growth suppressors, resisting apoptosis, replicative immortality, sustained angiogenesis, invasion & metastasis, avoiding immune destruction, deregulated cellular energetics, tumour promoting inflammation and genomic instability & mutation have been identified as hallmarks. These hallmarks are malignant behaviors are what makes the cell cancerous and the more extreme the behaviour the more aggressive the cancer the more likely the risk of a poor outcome. There are two primary genomic instability pathways: Microsatellite Instability (MSI) and Chromosomal Instability (CI) also referred to as Microsatellite Stability (MSS). Tumours arising by these pathways have a predilection for specific anatomical, histological and molecular biological features. It is possible that aberrant molecular expression of genes/proteins that promote malignant behaviors may also act as prognostic and predictive biomarkers, which may offer superior prognostic information to classical prognostic features. Cancer related inflammation has been described as a 7th hallmark of cancer. Despite the systemic inflammatory response (SIR) being associated with more aggressive malignant disease, infiltration by immune cells, particularly CD8+ lymphocytes, at the advancing edge of the tumour have been associated with improved outcome and tumour MSI. It remains unknown if the SIR is associated with tumour MSI and this requires further study. The mechanisms by which colorectal cancer cells locally invade through the bowel remain uncertain, but connective tissue degradation by matrix metalloproteinases (MMPs) such as MMP-9 have been implicated. MMP-9 has been found in the cancer cells, stromal cells and patient circulation. Although tumoural MMP-9 has been associated with poor survival, reports are conflicting and contain relatively small sample sizes. Furthermore, the influence of high serum MMP-9 on survival remains unknown. Src family kinases (SFKs) have been implicated in many adverse cancer cell behaviors. SFKs comprise 9 family members BLK, C-SRC, FGR, FYN, HCK, LCK, LYN, YES, YRK. C-SRC has been the most investigated of all SFKs, but the role of other SFKs in cellular behaviors and their prognostic value remains largely unknown. The development of Src inhibitors, such as Dasatinib, has identified SFKs as a potential therapeutic target for patients at higher risk of poor survival. Unfortunately, clinical trials so far have not been promising but this may reflect inadequate patient selection and SFKs may act as useful prognostic and predictive biomarkers. In chapter 3, the association between cancer related inflammation, tumour MSI, clinicopathological factors and survival was tested in two independent cohorts. A training cohort consisting of n=182 patients and a validation cohort of n=677 patients. MSI tumours were associated with a raised CRP (p=0.003). Hypoalbuminaemia was independently associated with poor overall survival in TNM stage II cancer (HR 3.04 (95% CI 1.44 – 6.43);p=0.004), poor recurrence free survival in TNM stage III cancer (HR 1.86 (95% 1.03 – 3.36);p=0.040) and poor overall survival in CI colorectal cancer (HR 1.49 (95% CI 1.06 – 2.10);p=0.022). Interestingly, MSI tumours were associated with poor overall survival in TNM stage III cancer (HR 2.20 (95% CI 1.10 – 4.37);p=0.025). In chapter 4, the role of MMP-9 in colorectal cancer progression and survival was examined. MMP-9 in the tissue was assessed using IHC and serum expression quantified using ELISA. Serum MMP-9 was associated with cancer cell expression (Spearman’s Correlation Coefficient (SCC) 0.393, p<0.001)) and stromal expression (SCC 0.319, p=0.002). Serum MMP-9 was associated with poor recurrence-free (HR 3.37 (95% CI 1.20 – 9.48);p=0.021) and overall survival (HR 3.16 (95% CI 1.22 – 8.15);p=0.018), but tumour MMP-9 was not survival or MSI status. In chapter 5, the role of SFK expression and activation in colorectal cancer progression and survival was studied. On PCR analysis, although LYN, C-SRC and YES were the most highly expressed, FGR and HCK had higher expression profiles as tumours progressed. Using IHC, raised cytoplasmic FAK (tyr 861) was independently associated with poor recurrence free survival in all cancers (HR 1.48 (95% CI 1.02 – 2.16);p=0.040) and CI cancers (HR 1.50 (95% CI 1.02 – 2.21);p=0.040). However, raised cytoplasmic HCK (HR 2.04 (95% CI 1.11 – 3.76);p=0.022) was independently associated with poor recurrence-free survival in TNM stage II cancers. T84 and HT29 cell lines were used to examine the cellular effects of Dasatinib. Cell viability was assessed using WST-1 assay and apoptosis assessed using an ELISA cell death detection assay. Dasatinib increased T84 tumour cell apoptosis in a dose dependent manner and resulted in reduced expression of nuclear (p=0.008) and cytoplasmic (p=0.016) FAK (tyr 861) expression and increased nuclear FGR expression (p=0.004). The results of this thesis confirm that colorectal cancer is a complex disease that represents several subtypes of cancer based on molecular biological behaviors. This thesis concentrated on features of the disease related to inflammation in terms of genetic and molecular characterisation. MSI cancers are closely associated with systemic inflammation but despite this observation, they retain their relatively improved survival. MMP-9 is a feature of tissue remodeling during inflammation and is also associated with degradation of connective tissue, advanced T-stage and poor outcome when measured in the serum. The lack of stromal quantification due to TMA use rather than full sections makes the value of tumoural MMP-9 immunoreactivity in the prognostication and its association with MSI unknown and requires further study. Finally, SFK activation was also associated with SIR, however, only cytoplasmic HCK was independently associated with poor survival in patients with TNM stage II disease, the group of patients where identifying a novel biomarker is most needed. There is still some way to go before these biomarkers are translated into clinical practice and future work needs to focus on obtaining a reliable and robust scientific technique with validation in an adequately powered independent cohort.

A principal component approach to space-based gravitational wave astronomy

The current approach to data analysis for the Laser Interferometry Space Antenna (LISA) depends on the time delay interferometry observables (TDI) which have to be generated before any weak signal detection can be performed. These are linear combinations of the raw data with appropriate time shifts that lead to the cancellation of the laser frequency noises. This is possible because of the multiple occurrences of the same noises in the different raw data. Originally, these observables were manually generated starting with LISA as a simple stationary array and then adjusted to incorporate the antenna's motions. However, none of the observables survived the flexing of the arms in that they did not lead to cancellation with the same structure. The principal component approach is another way of handling these noises that was presented by Romano and Woan which simplified the data analysis by removing the need to create them before the analysis. This method also depends on the multiple occurrences of the same noises but, instead of using them for cancellation, it takes advantage of the correlations that they produce between the different readings. These correlations can be expressed in a noise (data) covariance matrix which occurs in the Bayesian likelihood function when the noises are assumed be Gaussian. Romano and Woan showed that performing an eigendecomposition of this matrix produced two distinct sets of eigenvalues that can be distinguished by the absence of laser frequency noise from one set. The transformation of the raw data using the corresponding eigenvectors also produced data that was free from the laser frequency noises. This result led to the idea that the principal components may actually be time delay interferometry observables since they produced the same outcome, that is, data that are free from laser frequency noise. The aims here were (i) to investigate the connection between the principal components and these observables, (ii) to prove that the data analysis using them is equivalent to that using the traditional observables and (ii) to determine how this method adapts to real LISA especially the flexing of the antenna. For testing the connection between the principal components and the TDI observables a 10x 10 covariance matrix containing integer values was used in order to obtain an algebraic solution for the eigendecomposition. The matrix was generated using fixed unequal arm lengths and stationary noises with equal variances for each noise type. Results confirm that all four Sagnac observables can be generated from the eigenvectors of the principal components. The observables obtained from this method however, are tied to the length of the data and are not general expressions like the traditional observables, for example, the Sagnac observables for two different time stamps were generated from different sets of eigenvectors. It was also possible to generate the frequency domain optimal AET observables from the principal components obtained from the power spectral density matrix. These results indicate that this method is another way of producing the observables therefore analysis using principal components should give the same results as that using the traditional observables. This was proven by fact that the same relative likelihoods (within 0.3%) were obtained from the Bayesian estimates of the signal amplitude of a simple sinusoidal gravitational wave using the principal components and the optimal AET observables. This method fails if the eigenvalues that are free from laser frequency noises are not generated. These are obtained from the covariance matrix and the properties of LISA that are required for its computation are the phase-locking, arm lengths and noise variances. Preliminary results of the effects of these properties on the principal components indicate that only the absence of phase-locking prevented their production. The flexing of the antenna results in time varying arm lengths which will appear in the covariance matrix and, from our toy model investigations, this did not prevent the occurrence of the principal components. The difficulty with flexing, and also non-stationary noises, is that the Toeplitz structure of the matrix will be destroyed which will affect any computation methods that take advantage of this structure. In terms of separating the two sets of data for the analysis, this was not necessary because the laser frequency noises are very large compared to the photodetector noises which resulted in a significant reduction in the data containing them after the matrix inversion. In the frequency domain the power spectral density matrices were block diagonals which simplified the computation of the eigenvalues by allowing them to be done separately for each block. The results in general showed a lack of principal components in the absence of phase-locking except for the zero bin. The major difference with the power spectral density matrix is that the time varying arm lengths and non-stationarity do not show up because of the summation in the Fourier transform.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

Decision Matrix Compared with Partnering Principles

The ideas for this CRC research project are based directly on Sidwell, Kennedy and Chan (2002). That research examined a number of case studies to identify the characteristics of successful projects. The findings were used to construct a matrix of best practice project delivery strategies. The purpose of this literature review is to test the decision matrix against established theory and best practice in the subject of construction project management.

An inverse time admittance relay for fault detection in distribution networks containing DGs

Isolation of a faulted segment, from either side of a fault, in a radial feeder that has several converter interfaced DGs is a challenging task when current sensing protective devices are employed. The protective device, even if it senses a downstream fault, may not operate if fault current level is low due to the current limiting operation of converters. In this paper, a new inverse type relay is introduced based on line admittance measurement to protect a distribution network, which has several converter interfaced DGs. The basic operation of this relay, its grading and reach settings are explained. Moreover a method is proposed to compensate the fault resistance such that the relay operation under this condition is reliable. Then designed relay performances are evaluated in a radial distribution network. The results are validated through PSCAD/EMTDC simulation and MATLAB calculations.

Improved maritime target tracker using colour fusion

Searching for humans lost in vast stretches of ocean has always been a difficult task. This paper investigates a machine vision system that addresses this problem by exploiting the useful properties of alternate colour spaces. In particular, the paper investigates the fusion of colour information from the HSV, RGB, YCbCr and YIQ colour spaces within the emission matrix of a Hidden Markov Model tracker to enhance video based maritime target detection. The system has shown promising results. The paper also identifies challenges still needing to be met.

Relative entropy rate based multiple hidden Markov Model Approximation

This paper proposes a novel relative entropy rate (RER) based approach for multiple HMM (MHMM) approximation of a class of discrete-time uncertain processes. Under different uncertainty assumptions, the model design problem is posed either as a min-max optimisation problem or stochastic minimisation problem on the RER between joint laws describing the state and output processes (rather than the more usual RER between output processes). A suitable filter is proposed for which performance results are established which bound conditional mean estimation performance and show that estimation performance improves as the RER is reduced. These filter consistency and convergence bounds are the first results characterising multiple HMM approximation performance and suggest that joint RER concepts provide a useful model selection criteria. The proposed model design process and MHMM filter are demonstrated on an important image processing dim-target detection problem.

Completing the jigsaw : ESL and EFL undergraduate views on interactive peer-based learning

English as a Second Language (ESL) and English as a Foreign Language (EFL) students often face incongruence with Western teaching methods and learning expectations. The aim of this paper is to explore the potential for interactive peer-based learning to engage ESL and EFL language learners provide authentic communication experiences and accelerate learning through two case studies in different contexts. A study was undertaken to investigate student ‘voice’ (Rudduck, 1999, 2005; Rudduck & Flutter, 2004) during an intervention of communicative language teaching using peer-based learning strategies. This article describes unique similarities and subtle differences between ESL and EFL undergraduate learning in two different cultural contexts, using a 'stages of learning matrix' teaching tool to encourage civic skills and self-efficacy. It also suggests ways for teachers to improve on inconsistencies in group-based learning in order to promote more inclusive and congruent learning experiences for English language learners.

Study on the method of freeway incident detection using wireless positioning terminal

Improving the performance of a incident detection system was essential to minimize the effect of incidents. A new method of incident detection was brought forward in this paper based on an in-car terminal which consisted of GPS module, GSM module and control module as well as some optional parts such as airbag sensors, mobile phone positioning system (MPPS) module, etc. When a driver or vehicle discovered the freeway incident and initiated an alarm report the incident location information located by GPS, MPPS or both would be automatically send to a transport management center (TMC), then the TMC would confirm the accident with a closed-circuit television (CCTV) or other approaches. In this method, detection rate (DR), time to detect (TTD) and false alarm rate (FAR) were more important performance targets. Finally, some feasible means such as management mode, education mode and suitable accident confirming approaches had been put forward to improve these targets.

Processing of polycaprolactone and polycaprolactone-based copolymers into 3D scaffolds and their cellular responses

Synthetic polymers have attracted much attention in tissue engineering due to their ability to modulate biomechanical properties. This study investigated the feasibility of processing poly(varepsilon-caprolactone) (PCL) homopolymer, PCL-poly(ethylene glycol) (PEG) diblock, and PCL-PEG-PCL triblock copolymers into three-dimensional porous scaffolds. Properties of the various polymers were investigated by dynamic thermal analysis. The scaffolds were manufactured using the desktop robot-based rapid prototyping technique. Gross morphology and internal three-dimensional structure of scaffolds were identified by scanning electron microscopy and micro-computed tomography, which showed excellent fusion at the filament junctions, high uniformity, and complete interconnectivity of pore networks. The influences of process parameters on scaffolds' morphological and mechanical characteristics were studied. Data confirmed that the process parameters directly influenced the pore size, porosity, and, consequently, the mechanical properties of the scaffolds. The in vitro cell culture study was performed to investigate the influence of polymer nature and scaffold architecture on the adhesion of the cells onto the scaffolds using rabbit smooth muscle cells. Light, scanning electron, and confocal laser microscopy showed cell adhesion, proliferation, and extracellular matrix formation on the surface as well as inside the structure of both scaffold groups. The completely interconnected and highly regular honeycomb-like pore morphology supported bridging of the pores via cell-to-cell contact as well as production of extracellular matrix at later time points. The results indicated that the incorporation of hydrophilic PEG into hydrophobic PCL enhanced the overall hydrophilicity and cell culture performance of PCL-PEG copolymer. However, the scaffold architecture did not significantly influence the cell culture performance in this study.