Investigating the evolution and stability of a resource limited artificial immune system.

Timmis J and Neal M J. Investigating the evolution and stability of a resource limited artificial immune system. In Proceedings of GECCO - special workshop on artificial immune systems, pages 40-41. AAAI press, 2000.

FRANTIC - A system for inducing accurate and comprehensible fuzzy rules

M. Galea and Q. Shen. FRANTIC - A system for inducing accurate and comprehensible fuzzy rules. Proceedings of the 2004 UK Workshop on Computational Intelligence, pages 136-143.

Cellular automata and non-static image processing for embodied robot systems on a massively parallel processor array

Huelse, M, Barr, D R W, Dudek, P: Cellular Automata and non-static image processing for embodied robot systems on a massively parallel processor array. In: Adamatzky, A et al. (eds) AUTOMATA 2008, Theory and Applications of Cellular Automata. Luniver Press, 2008, pp. 504-510. Sponsorship: EPSRC

A role for LH in the regulation of expression of mRNAs encoding components of the insulin-like growth factor (IGF) system in the ovine corpus luteum

P.M. Hastie and W. Haresign (2006). A role for LH in the regulation of expression of mRNAs encoding components of the insulin-like growth factor (IGF) system in the ovine corpus luteum. Animal Reproduction Science, 96(1-2), 196-209. Sponsorship: DEFRA RAE2008

Mermera: Non-Coherent Distributed Shared Memory for Parallel Computing

The proliferation of inexpensive workstations and networks has prompted several researchers to use such distributed systems for parallel computing. Attempts have been made to offer a shared-memory programming model on such distributed memory computers. Most systems provide a shared-memory that is coherent in that all processes that use it agree on the order of all memory events. This dissertation explores the possibility of a significant improvement in the performance of some applications when they use non-coherent memory. First, a new formal model to describe existing non-coherent memories is developed. I use this model to prove that certain problems can be solved using asynchronous iterative algorithms on shared-memory in which the coherence constraints are substantially relaxed. In the course of the development of the model I discovered a new type of non-coherent behavior called Local Consistency. Second, a programming model, Mermera, is proposed. It provides programmers with a choice of hierarchically related non-coherent behaviors along with one coherent behavior. Thus, one can trade-off the ease of programming with coherent memory for improved performance with non-coherent memory. As an example, I present a program to solve a linear system of equations using an asynchronous iterative algorithm. This program uses all the behaviors offered by Mermera. Third, I describe the implementation of Mermera on a BBN Butterfly TC2000 and on a network of workstations. The performance of a version of the equation solving program that uses all the behaviors of Mermera is compared with that of a version that uses coherent behavior only. For a system of 1000 equations the former exhibits at least a 5-fold improvement in convergence time over the latter. The version using coherent behavior only does not benefit from employing more than one workstation to solve the problem while the program using non-coherent behavior continues to achieve improved performance as the number of workstations is increased from 1 to 6. This measurement corroborates our belief that non-coherent shared memory can be a performance boon for some applications.

New Notions of Reduction and Non-Semantic Proofs of β-Strong Normalization in Typed λ-Calculi

Two new notions of reduction for terms of the λ-calculus are introduced and the question of whether a λ-term is beta-strongly normalizing is reduced to the question of whether a λ-term is merely normalizing under one of the new notions of reduction. This leads to a new way to prove beta-strong normalization for typed λ-calculi. Instead of the usual semantic proof style based on Girard's "candidats de réductibilité'', termination can be proved using a decreasing metric over a well-founded ordering in a style more common in the field of term rewriting. This new proof method is applied to the simply-typed λ-calculus and the system of intersection types.

The Construction of Arbitrary Stable Dynamics in Non-Linear Neural Networks

In this paper, two methods for constructing systems of ordinary differential equations realizing any fixed finite set of equilibria in any fixed finite dimension are introduced; no spurious equilibria are possible for either method. By using the first method, one can construct a system with the fewest number of equilibria, given a fixed set of attractors. Using a strict Lyapunov function for each of these differential equations, a large class of systems with the same set of equilibria is constructed. A method of fitting these nonlinear systems to trajectories is proposed. In addition, a general method which will produce an arbitrary number of periodic orbits of shapes of arbitrary complexity is also discussed. A more general second method is given to construct a differential equation which converges to a fixed given finite set of equilibria. This technique is much more general in that it allows this set of equilibria to have any of a large class of indices which are consistent with the Morse Inequalities. It is clear that this class is not universal, because there is a large class of additional vector fields with convergent dynamics which cannot be constructed by the above method. The easiest way to see this is to enumerate the set of Morse indices which can be obtained by the above method and compare this class with the class of Morse indices of arbitrary differential equations with convergent dynamics. The former set of indices are a proper subclass of the latter, therefore, the above construction cannot be universal. In general, it is a difficult open problem to construct a specific example of a differential equation with a given fixed set of equilibria, permissible Morse indices, and permissible connections between stable and unstable manifolds. A strict Lyapunov function is given for this second case as well. This strict Lyapunov function as above enables construction of a large class of examples consistent with these more complicated dynamics and indices. The determination of all the basins of attraction in the general case for these systems is also difficult and open.

The Synthesis of Arbitrary Stable Dynamics in Non-linear Neural Networks II: Feedback and Universality

We wish to construct a realization theory of stable neural networks and use this theory to model the variety of stable dynamics apparent in natural data. Such a theory should have numerous applications to constructing specific artificial neural networks with desired dynamical behavior. The networks used in this theory should have well understood dynamics yet be as diverse as possible to capture natural diversity. In this article, I describe a parameterized family of higher order, gradient-like neural networks which have known arbitrary equilibria with unstable manifolds of known specified dimension. Moreover, any system with hyperbolic dynamics is conjugate to one of these systems in a neighborhood of the equilibrium points. Prior work on how to synthesize attractors using dynamical systems theory, optimization, or direct parametric. fits to known stable systems, is either non-constructive, lacks generality, or has unspecified attracting equilibria. More specifically, We construct a parameterized family of gradient-like neural networks with a simple feedback rule which will generate equilibrium points with a set of unstable manifolds of specified dimension. Strict Lyapunov functions and nested periodic orbits are obtained for these systems and used as a method of synthesis to generate a large family of systems with the same local dynamics. This work is applied to show how one can interpolate finite sets of data, on nested periodic orbits.

Characterisation of the non-muscle α-actinins

Actinins are cytoskeleton proteins that cross-link actin filaments. Evolution of the actinin family resulted in the formation of Ca++-insensitive muscle isoforms (actinin-2 and- 3) and Ca++-sensitive non-muscle isoforms (actinin-1 and -4) with regard to their actin-binding function. Despite high sequence similarity, unique properties have been ascribed to actinin-4 compared with actinin-1. Actinin-4 is the predominant isoform reported to be associated with the cancer phenotype. Actinin-4, but not actinin-1, is essential for normal glomerular function in the kidney and and is able to translocate to the nucleus to regulate transcription. To understand the molecular basis for such isoform-specific functions I have comprehensively compared these proteins in terms of localisation, migration, alternative splicing, actin-binding properties, heterodimer formation and molecular interactions for the first time. This work characterises a number of commercially available actinin antibodies and in doing so, identifies actinin-1, -2 and -4 isoform-specific antibodies that enabled studies of actinin expression and localisation. This work identifies the actinin rod domain as the predominant domain that influences actinin localisation however localisation is likely to be effected by the entire actinin protein. si-RNA- mediated knockdown of actinin-1 and -4 did not affect migration in a number of cell lines highlighting that migration may only require a fraction of total non-muscle actinin levels. This work finds that the Ca++-insensitive variant of actinin-4 is expressed only in the nervous system and thus cannot be regarded as a smooth muscle isoform, as is the case for the Ca++-insensitive variant of actinin-1. This work also identifies a previously unreported exon 19a+19b expressing variant of actinin-4 in human skeletal muscle. This work finds that alternative splice variants of actinin-1 and -4 are co-expressed in a number of tissues, in particular the brain. In contrast to healthy brain, glioblastoma cells express Ca++-sensitive variants of both actinin-1 and -4. Actin-binding properties of actinin-1 and -4 are similar and are unlikely to explain isoform-specific functions. Surprisingly, this work reveals that actinin-1/-4 heterodimers, rather than homodimers, are the most abundant form of actinin in many cancer cell lines. Taken together this data suggests that actinin-1 and -4 cannot be viewed as distinct entities from each other but rather as proteins that can exist in both homodimeric and heterodimeric forms. Finally, this work employs yeast two-hybrid and proteomic approaches to identify actinin-interacting proteins. In doing so, this work identifies a number of putative actinin-4 specific interacting partners that may help to explain some of the unique functions attributed the actinin-4. The observation of alternative splice variants of actinin-1 and -4 combined with the observed potential of these proteins to form homodimers and heterodimers suggests that homodimers and heterodimers with novel actin-binding properties and interaction networks may exist. The ability to behave in this manner may have functional implications. This may be of importance considering that these proteins are central to such processes as cell migration and adhesion. This significantly alters our view of the non-muscle actinins.

Modified cyclodextrins as novel non-viral vectors for neuronal siRNA delivery: focus on Huntington’s disease

Huntington’s Disease (HD) is a rare autosomal dominant neurodegenerative disease caused by the expression of a mutant Huntingtin (muHTT) protein. Therefore, preventing the expression of muHTT by harnessing the specificity of the RNA interference (RNAi) pathway is a key research avenue for developing novel therapies for HD. However, the biggest caveat in the RNAi approach is the delivery of short interfering RNA (siRNAs) to neurons, which are notoriously difficult to transfect. Indeed, despite the great advances in the field of nanotechnology, there remains a great need to develop more effective and less toxic carriers for siRNA delivery to the Central Nervous System (CNS). Thus, the aim of this thesis was to investigate the utility of modified amphiphilic β-cyclodextrins (CDs), oligosaccharide-based molecules, as non-viral vectors for siRNA delivery for HD. Modified CDs were able to bind and complex siRNAs forming nanoparticles capable of delivering siRNAs to ST14A-HTT120Q cells and to human HD fibroblasts, and reducing the expression of the HTT gene in these in vitro models of HD. Moreover, direct administration of CD.siRNA nanoparticles into the R6/2 mouse brain resulted in significant HTT gene expression knockdown and selective alleviation of rotarod motor deficits in this mouse model of HD. In contrast to widely used transfection reagents, CD.siRNA nanoparticles only induced limited cytotoxic and neuroinflammatory responses in multiple brain-derived cell-lines, and also in vivo after single direct injections into the mouse brain. Alternatively, we have also described a PEGylation-based formulation approach to further stabilise CD.siRNA nanoparticles and progress towards a systemic delivery nanosystem. Resulting PEGylated CD.siRNA nanoparticles showed increased stability in physiological saltconditions and, to some extent, reduced protein-induced aggregation. Taken together, the work outlined in this thesis identifies modified CDs as effective, safe and versatile siRNA delivery systems that hold great potential for the treatment of CNS disorders, such as HD.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Cost savings from relaxation of operational constraints on a power system with high wind penetration

Wind energy is predominantly a nonsynchronous generation source. Large-scale integration of wind generation with existing electricity systems, therefore, presents challenges in maintaining system frequency stability and local voltage stability. Transmission system operators have implemented system operational constraints (SOCs) in order to maintain stability with high wind generation, but imposition of these constraints results in higher operating costs. A mixed integer programming tool was used to simulate generator dispatch in order to assess the impact of various SOCs on generation costs. Interleaved day-ahead scheduling and real-time dispatch models were developed to allow accurate representation of forced outages and wind forecast errors, and were applied to the proposed Irish power system of 2020 with a wind penetration of 32%. Savings of at least 7.8% in generation costs and reductions in wind curtailment of 50% were identified when the most influential SOCs were relaxed. The results also illustrate the need to relax local SOCs together with the system-wide nonsynchronous penetration limit SOC, as savings from increasing the nonsynchronous limit beyond 70% were restricted without relaxation of local SOCs. The methodology and results allow for quantification of the costs of SOCs, allowing the optimal upgrade path for generation and transmission infrastructure to be determined.

Investigation of population genetic structure and mating system in the ant Pheidole pallidula

The origin of eusociality in haplo-diploid organisms such as Hymenoptera has been mostly explained by kin selection. However, several studies have uncovered decreased relatedness values within colonies, resulting primarily from multiple queen matings (polyandry) and/or from the presence of more than one functional queen (polygyny). Here, we report on the use of microsatellite data for the investigation of sociogenetic parameters, such as relatedness, and levels of polygyny and polyandry, in the ant Pheidole pallidula. We demonstrate, through analysis of mother-offspring combinations and the use of direct sperm typing, that each queen is inseminated by a single male. The inbreeding coefficient within colonies and the levels of relatedness between the queens and their mate are not significantly different from zero, indicating that matings occur between unrelated individuals. Analyses of worker genotypes demonstrate that 38% of the colonies are polygynous with 2-4 functional queens, and suggest the existence of reproductive skew, i.e. unequal respective contribution of queens to reproduction. Finally, our analyses indicate that colonies are genetically differentiated and form a population exhibiting significant isolation-by-distance, suggesting that some colonies originate through budding.

A novel, non-apoptotic role for Scythe/BAT3: a functional switch between the pro- and anti-proliferative roles of p21 during the cell cycle.

BACKGROUND: Scythe/BAT3 is a member of the BAG protein family whose role in apoptosis has been extensively studied. However, since the developmental defects observed in Bat3-null mouse embryos cannot be explained solely by defects in apoptosis, we investigated whether BAT3 is also involved in cell-cycle progression. METHODS/PRINCIPAL FINDINGS: Using a stable-inducible Bat3-knockdown cellular system, we demonstrated that reduced BAT3 protein level causes a delay in both G1/S transition and G2/M progression. Concurrent with these changes in cell-cycle progression, we observed a reduction in the turnover and phosphorylation of the CDK inhibitor p21, which is best known as an inhibitor of DNA replication; however, phosphorylated p21 has also been shown to promote G2/M progression. Our findings indicate that in Bat3-knockdown cells, p21 continues to be synthesized during cell-cycle phases that do not normally require p21, resulting in p21 protein accumulation and a subsequent delay in cell-cycle progression. Finally, we showed that BAT3 co-localizes with p21 during the cell cycle and is required for the translocation of p21 from the cytoplasm to the nucleus during the G1/S transition and G2/M progression. CONCLUSION: Our study reveals a novel, non-apoptotic role for BAT3 in cell-cycle regulation. By maintaining a low p21 protein level during the G1/S transition, BAT3 counteracts the inhibitory effect of p21 on DNA replication and thus enables the cells to progress from G1 to S phase. Conversely, during G2/M progression, BAT3 facilitates p21 phosphorylation by cyclin A/Cdk2, an event required for G2/M progression. BAT3 modulates these pro- and anti-proliferative roles of p21 at least in part by regulating cyclin A abundance, as well as p21 translocation between the cytoplasm and the nucleus to ensure that it functions in the appropriate intracellular compartment during each phase of the cell cycle.

Waveguide QED: Many-body bound-state effects in coherent and Fock-state scattering from a two-level system

Strong coupling between a two-level system (TLS) and bosonic modes produces dramatic quantum optics effects. We consider a one-dimensional continuum of bosons coupled to a single localized TLS, a system which may be realized in a variety of plasmonic, photonic, or electronic contexts. We present the exact many-body scattering eigenstate obtained by imposing open boundary conditions. Multiphoton bound states appear in the scattering of two or more photons due to the coupling between the photons and the TLS. Such bound states are shown to have a large effect on scattering of both Fock- and coherent-state wave packets, especially in the intermediate coupling-strength regime. We compare the statistics of the transmitted light with a coherent state having the same mean photon number: as the interaction strength increases, the one-photon probability is suppressed rapidly, and the two- and three-photon probabilities are greatly enhanced due to the many-body bound states. This results in non-Poissonian light. © 2010 The American Physical Society.