Development of an app to support learning in A-level maths

This project involved producing an app for smart devices to enable modernised learning for A-level maths students. Research in a stakeholder school showed that 94% of pupils surveyed within the upper-secondary level owned a smartphone and most owned a tablet also, emphasising the opportunity for using apps to support learning. The app was developed using iBuildApp, an online app-creation programme which requires no programming. Past exam questions and solutions, notes and video tutorials were included and the topic was vectors, identified by teachers as problematic. Pupils generally found the app easy to use and wanted further development. The videos were popular despite this not ranking highly as a preferred method of revision previously. Teachers were happy for pupils to use the app to supplement their learning, both in the classroom and outside.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Shocks in unmagnetized plasma with a shear flow: Stability and magnetic field generation

A pair of curved shocks in a collisionless plasma is examined with a two-dimensional particle-in-cell simulation. The shocks are created by the collision of two electron-ion clouds at a speed that exceeds everywhere the threshold speed for shock formation. A variation of the collision speed along the initially planar collision boundary, which is comparable to the ion acoustic speed, yields a curvature of the shock that increases with time. The spatially varying Mach number of the shocks results in a variation of the downstream density in the direction along the shock boundary. This variation is eventually equilibrated by the thermal diffusion of ions. The pair of shocks is stable for tens of inverse ion plasma frequencies. The angle between the mean flow velocity vector of the inflowing upstream plasma and the shock's electrostatic field increases steadily during this time. The disalignment of both vectors gives rise to a rotational electron flow, which yields the growth of magnetic field patches that are coherent over tens of electron skin depths.

Clinical potential of gene-directed enzyme prodrug therapy to improve radiation therapy in prostate cancer patients

Despite the advances in prostate cancer diagnosis and treatment, current therapies are not curative in a significant proportion of patients. Gene-directed enzyme prodrug therapy (GDEPT), when combined with radiation therapy, could improve the outcome of treatment for prostate cancer, the second leading cause of cancer death in the western world. GDEPT involves the introduction of a therapeutic transgene, which can be targeted to the tumour cells. A prodrug is administered systemically and is converted to its toxic form only in those cells containing the transgene, resulting in cell kill. This review will discuss the clinical trials which have investigated the potential of GDEPT at various stages of prostate cancer progression. The advantages of using GDEPT in combination with radiotherapy will be examined, as well as some of the recent advances which enhance the potential utility of GDEPT.

Hypoxia response element-driven cytosine deaminase/5-fluorocytosine gene therapy system:a highly effective approach to overcome the dynamics of tumour hypoxia and enhance the radiosensitivity of prostate cancer cells in vitro

BACKGROUND: We proposed to exploit hypoxia-inducible factor (HIF)-1alpha overexpression in prostate tumours and use this transcriptional machinery to control the expression of the suicide gene cytosine deaminase (CD) through binding of HIF-1alpha to arrangements of hypoxia response elements. CD is a prodrug activation enzyme, which converts inactive 5-fluorocytosine to active 5-fluorouracil (5-FU), allowing selective killing of vector containing cells.

METHODS: We developed a pair of vectors, containing either five or eight copies of the hypoxia response element (HRE) isolated from the vascular endothelial growth factor (pH5VCD) or glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (pH8GCD) gene, respectively. The kinetics of the hypoxic induction of the vectors and sensitization effects were evaluated in 22Rv1 and DU145 cells in vitro.

RESULTS: The CD protein as selectively detected in lysates of transiently transfected 22Rv1 and DU145 cells following hypoxic exposure. This is the first evidence of GAPDH HREs being used to control a suicide gene therapy strategy. Detectable CD levels were sustained upon reoxygenation and prolonged hypoxic exposures. Hypoxia-induced chemoresistance to 5-FU was overcome in both cell lines treated with this suicide gene therapy approach. Hypoxic transfectants were sensitized to prodrug concentrations that were ten-fold lower than those that are clinically relevant. Moreover, the surviving fraction of reoxygenated transfectants could be further reduced with the concomitant delivery of clinically relevant single radiation doses.

CONCLUSIONS: This strategy thus has the potential to sensitize the hypoxic compartment of prostate tumours and improve the outcome of current therapies.

Gene-based therapy in prostate cancer

Prostate cancer is one of the commonest causes of illness and death from cancer. Radical prostatectomy, radiotherapy, and hormonal therapy are the main conventional treatments. However, gene therapy is emerging as a promising adjuvant to conventional strategies, and several clinical trials are in progress. Here, we outline several approaches to gene therapy for prostate cancer that have been investigated. Methods of gene delivery are described, particularly those that have commonly been used in research on prostate cancer. We discuss efforts to achieve tissue-specific gene delivery, focusing on the use of tissue-specific gene promoters. Finally, the present use of gene therapy for prostate cancer is evaluated. The ability to deliver gene-therapy vectors directly to prostate tissue, and to regulate gene expression in a tissue-specific manner, offers promise for the use of gene therapy in prostate cancer.

Towards a Cyber-physical Resilience Framework for Smart Grids

As modern power grids move towards becoming a smart grid, there is an increasing reliance on the data that is transmitted and processed by ICT systems. This reliance introduces new digital attack vectors. Many of the proposed approaches that aim to address this problem largely focus on applying well-known ICT security solutions. However, what is needed are approaches that meet the complex concerns of the smart grid as a cyber-physical system. Furthermore, to support the automatic control loops that exist in a power grid, similarly automatic security and resilience mechanisms are needed that rely on minimal operator intervention. The research proposed in this paper aims to develop a framework that ensures resilient smart grid operation in light of successful cyber-attacks.

Seasonality of Plasmodium falciparum transmission: a systematic review

Background: Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized. 

Methods: The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts. 

Results and discussion: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both). 

Discussion: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location. 

Conclusions: The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales.

Multifunctional Delivery Systems for Cancer Gene Therapy

This chapter examines key concepts with respect to cancer gene therapy and the current issues with respect to non-viral delivery. The biological and molecular barriers that need to be overcome before effective non-viral delivery systems can be appropriately designed for oncology applications are highlighted and ways to overcome these are discussed. Strategies developed to evade the immune response are also described and targeted gene delivery is examined with the most effective strategies highlighted. Finally, this chapter proposes a new way forward based on a growing body of evidence that supports a multifunctional delivery approach involving the creation of vectors, with a unique molecular architecture designed using a bottom-up approach.

A Compositional and Interpretable Semantic Space

Vector Space Models (VSMs) of Semantics are useful tools for exploring the semantics of single words, and the composition of words to make phrasal meaning. While many methods can estimate the meaning (i.e. vector) of a phrase, few do so in an interpretable way. We introduce a new method (CNNSE) that allows word and phrase vectors to adapt to the notion of composition. Our method learns a VSM that is both tailored to support a chosen semantic composition operation, and whose resulting features have an intuitive interpretation. Interpretability allows for the exploration of phrasal semantics, which we leverage to analyze performance on a behavioral task.

Geostatistical Fisher discriminant analysis

A geostatistical version of the classical Fisher rule (linear discriminant analysis) is presented.This method is applicable when a large dataset of multivariate observations is available within a domain split in several known subdomains, and it assumes that the variograms (or covariance functions) are comparable between subdomains, which only differ in the mean values of the available variables. The method consists on finding the eigen-decomposition of the matrix W-1B, where W is the matrix of sills of all direct- and cross-variograms, and B is the covariance matrix of the vectors of weighted means within each subdomain, obtained by generalized least squares. The method is used to map peat blanket occurrence in Northern Ireland, with data from the Tellus
survey, which requires a minimal change to the general recipe: to use compositionally-compliant variogram tools and models, and work with log-ratio transformed data.

Calmodulin disruption impacts growth and motility in juvenile liver fluke

Background: Deficiencies in effective flukicide options and growing issues with drug resistance make current strategies for liver fluke control unsustainable, thereby promoting the need to identify and validate new control targets in Fasciola spp. parasites. Calmodulins (CaMs) are small calcium-sensing proteins with ubiquitous expression in all eukaryotic organisms and generally use fluctuations in intracellular calcium levels to modulate cell signalling events. CaMs are essential for fundamental processes including the phosphorylation of protein kinases, gene transcription, calcium transport and smooth muscle contraction. In the blood fluke Schistosoma mansoni, calmodulins have been implicated in egg hatching, miracidial transformation and larval development. Previously, CaMs have been identified amongst liver fluke excretory-secretory products and three CaM-like proteins have been characterised biochemically from adult Fasciola hepatica, although their functions remain unknown.

Methods: In this study, we set out to investigate the biological function and control target potential of F. hepatica CaMs (FhCaMs) using RNAi methodology alongside novel in vitro bioassays.

Results: Our results reveal that: (i) FhCaMs are widely expressed in parenchymal cells throughout the forebody region of juvenile fluke; (ii) significant transcriptional knockdown of FhCaM1-3 was inducible by exposure to either long (~200 nt) double stranded (ds) RNAs or 27 nt short interfering (si) RNAs, although siRNAs were less effective than long dsRNAs; (iii) transient long dsRNA exposure-induced RNA interference (RNAi) of FhCaMs triggered transcript knockdown that persisted for ≥ 21 days, and led to detectable suppression of FhCaM proteins; (iv) FhCaM RNAi significantly reduced the growth of juvenile flukes maintained in vitro; (v) FhCaM RNAi juveniles also displayed hyperactivity encompassing significantly increased migration; (vi) both the reduced growth and increased motility phenotypes were recapitulated in juvenile fluke using the CaM inhibitor trifluoperazine hydrochloride, supporting phenotype specificity.

Conclusions: These data indicate that the Ca(2+)-modulating functions of FhCaMs are important for juvenile fluke growth and movement and provide the first functional genomics-based example of a growth-defect resulting from gene silencing in liver fluke. Whilst the phenotypic impacts of FhCaM silencing on fluke behaviour do not strongly support their candidature as new flukicide targets, the growth impacts encourage further consideration, especially in light of the speed of juvenile fluke growth in vivo.

Ferroelectric Vortices and Related Configurations

This chapter discusses that the theoretical studies, using both atomistic and phenomenological approaches, have made clear predictions about the existence and behaviour of ferroelectric (FE) vortices. Effective Hamiltonians can be implemented within both Monte Carlo (MC) and molecular dynamics (MD) simulations. In contrast to the effective Hamiltonian method, which is atomistic in nature, the phase field method employs a continuum approach, in which the polarization field is the order parameter. Properties of FE nanostructures are largely governed by the existence of a depolarization field, which is much stronger than the demagnetization field in magnetic nanosystems. The topological patterns seen in rare earth manganites are often referred to as vortices and yet this claim never seems to be explicitly justified. By inspection, the form of a vortex structure is such that there is a continuous rotation in the orientation of dipole vectors around the singularity at the centre of the vortex.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.