Biodiversity change in the Irish uplands - the effects of grazing management

As a prominent form of land use across much of upland Europe, extensive livestock grazing may hold the key to the sustainable management of these landscapes. Recent agricultural policy reform, however, has resulted in a decline in upland sheep numbers, prompting concern for the biodiversity value of these areas. This study quantifies the effects of varying levels of grazing management on plant, ground beetle and breeding bird diversity and assemblage in the uplands and lowlands of hill sheep farms in County Kerry, Ireland. Farms represent a continuum of light to heavy grazing, measured using a series of field indicators across several habitats, such as the internationally important blanket bog, home to the ground beetle, Carabus clatratus. Linear mixed effects modelling and non-metric multidimensional scaling are employed to disentangle the most influential management and environmental factors. Grazing state may be determined by the presence of Molinia caerulea or Nardus stricta, and variables such as % traditional ewes, % vegetation litter and % scrub prove valuable indicators of diversity. Measures of ecosystem functioning, e.g. plant biomass (nutrient cycling) and % vegetation cover (erosion rates) are influenced by plant diversity, which is influenced by grazing management. Levels of the ecosystem service, soil organic carbon, vary with ground beetle abundance and diversity, potentially influencing carbon sequestration and thereby climate change. The majority of species from all three taxa are found in the lowlands, with the exception of birds such as meadow pipit and skylark. The scale of measurement should be determined by the size and mobility of the species in question. The challenge is to manage these high nature value landscapes using agri-environment schemes which enhance biodiversity by maintaining structural heterogeneity across a range of scales, altitudes and habitats whilst integrating the decisions of people living and working in these marginal areas.

High speed nonlinear optical components for next-generation optical communications

Electronic signal processing systems currently employed at core internet routers require huge amounts of power to operate and they may be unable to continue to satisfy consumer demand for more bandwidth without an inordinate increase in cost, size and/or energy consumption. Optical signal processing techniques may be deployed in next-generation optical networks for simple tasks such as wavelength conversion, demultiplexing and format conversion at high speed (≥100Gb.s-1) to alleviate the pressure on existing core router infrastructure. To implement optical signal processing functionalities, it is necessary to exploit the nonlinear optical properties of suitable materials such as III-V semiconductor compounds, silicon, periodically-poled lithium niobate (PPLN), highly nonlinear fibre (HNLF) or chalcogenide glasses. However, nonlinear optical (NLO) components such as semiconductor optical amplifiers (SOAs), electroabsorption modulators (EAMs) and silicon nanowires are the most promising candidates as all-optical switching elements vis-à-vis ease of integration, device footprint and energy consumption. This PhD thesis presents the amplitude and phase dynamics in a range of device configurations containing SOAs, EAMs and/or silicon nanowires to support the design of all optical switching elements for deployment in next-generation optical networks. Time-resolved pump-probe spectroscopy using pulses with a pulse width of 3ps from mode-locked laser sources was utilized to accurately measure the carrier dynamics in the device(s) under test. The research work into four main topics: (a) a long SOA, (b) the concatenated SOA-EAMSOA (CSES) configuration, (c) silicon nanowires embedded in SU8 polymer and (d) a custom epitaxy design EAM with fast carrier sweepout dynamics. The principal aim was to identify the optimum operation conditions for each of these NLO device configurations to enhance their switching capability and to assess their potential for various optical signal processing functionalities. All of the NLO device configurations investigated in this thesis are compact and suitable for monolithic and/or hybrid integration.

Simplified decoding techniques for linear block codes

Error correcting codes are combinatorial objects, designed to enable reliable transmission of digital data over noisy channels. They are ubiquitously used in communication, data storage etc. Error correction allows reconstruction of the original data from received word. The classical decoding algorithms are constrained to output just one codeword. However, in the late 50’s researchers proposed a relaxed error correction model for potentially large error rates known as list decoding. The research presented in this thesis focuses on reducing the computational effort and enhancing the efficiency of decoding algorithms for several codes from algorithmic as well as architectural standpoint. The codes in consideration are linear block codes closely related to Reed Solomon (RS) codes. A high speed low complexity algorithm and architecture are presented for encoding and decoding RS codes based on evaluation. The implementation results show that the hardware resources and the total execution time are significantly reduced as compared to the classical decoder. The evaluation based encoding and decoding schemes are modified and extended for shortened RS codes and software implementation shows substantial reduction in memory footprint at the expense of latency. Hermitian codes can be seen as concatenated RS codes and are much longer than RS codes over the same aphabet. A fast, novel and efficient VLSI architecture for Hermitian codes is proposed based on interpolation decoding. The proposed architecture is proven to have better than Kötter’s decoder for high rate codes. The thesis work also explores a method of constructing optimal codes by computing the subfield subcodes of Generalized Toric (GT) codes that is a natural extension of RS codes over several dimensions. The polynomial generators or evaluation polynomials for subfield-subcodes of GT codes are identified based on which dimension and bound for the minimum distance are computed. The algebraic structure for the polynomials evaluating to subfield is used to simplify the list decoding algorithm for BCH codes. Finally, an efficient and novel approach is proposed for exploiting powerful codes having complex decoding but simple encoding scheme (comparable to RS codes) for multihop wireless sensor network (WSN) applications.

Development of CMOS-compatible electrostatic supercapacitors

This work focuses on development of electrostatic supercapacitors (ESCs) using process routes compatible with complementary metal–oxide–semiconductor (CMOS) fabrication. Wafer-scale anodised aluminium oxide (AAO) processing techniques have been developed to produce high-surface area templates. Statistically optimised atomic layer deposition (ALD) processes have been developed to conformally coat the templates and generate metalinsulator-metal capacitor structures. Detailed electrical characterisation and analysis for a range of devices, revealed ESC’s with high capacitance densities of ~12 μF cm-2 and equivalent energy densities of 0.28 Wh/kg . Finally the suitability of ESC’s toward next generation energy storage applications is discussed.

Simulation of multigate SOI transistors with silicon, germanium and III-V channels

In this work by employing numerical three-dimensional simulations we study the electrical performance and short channel behavior of several multi-gate transistors based on advanced SOI technology. These include FinFETs, triple-gate and gate-all-around nanowire FETs with different channel material, namely Si, Ge, and III-V compound semiconductors, all most promising candidates for future nanoscale CMOS technologies. Also, a new type of transistor called “junctionless nanowire transistor” is presented and extensive simulations are carried out to study its electrical characteristics and compare with the conventional inversion- and accumulation-mode transistors. We study the influence of device properties such as different channel material and orientation, dimensions, and doping concentration as well as quantum effects on the performance of multi-gate SOI transistors. For the modeled n-channel nanowire devices we found that at very small cross sections the nanowires with silicon channel are more immune to short channel effects. Interestingly, the mobility of the channel material is not as significant in determining the device performance in ultrashort channels as other material properties such as the dielectric constant and the effective mass. Better electrostatic control is achieved in materials with smaller dielectric constant and smaller source-to-drain tunneling currents are observed in channels with higher transport effective mass. This explains our results on Si-based devices. In addition to using the commercial TCAD software (Silvaco and Synopsys TCAD), we have developed a three-dimensional Schrödinger-Poisson solver based on the non-equilibrium Green’s functions formalism and in the framework of effective mass approximation. This allows studying the influence of quantum effects on electrical performance of ultra-scaled devices. We have implemented different mode-space methodologies in our 3D quantum-mechanical simulator and moreover introduced a new method to deal with discontinuities in the device structures which is much faster than the coupled-mode-space approach.

Properties and applications of injection locking in 1.55 μm quantum-dash mode-locked semiconductor lasers

Mode-locked semiconductor lasers are compact pulsed sources with ultra-narrow pulse widths and high repetition-rates. In order to use these sources in real applications, their performance needs to be optimised in several aspects, usually by external control. We experimentally investigate the behaviour of recently-developed quantum-dash mode-locked lasers (QDMLLs) emitting at 1.55 μm under external optical injection. Single-section and two-section lasers with different repetition frequencies and active-region structures are studied. Particularly, we are interested in a regime which the laser remains mode-locked and the individual modes are simultaneously phase-locked to the external laser. Injection-locked self-mode-locked lasers demonstrate tunable microwave generation at first or second harmonic of the free-running repetition frequency with sub-MHz RF linewidth. For two-section mode-locked lasers, using dual-mode optical injection (injection of two coherent CW lines), narrowing the RF linewidth close to that of the electrical source, narrowing the optical linewidths and reduction in the time-bandwidth product is achieved. Under optimised bias conditions of the slave laser, a repetition frequency tuning ratio >2% is achieved, a record for a monolithic semiconductor mode-locked laser. In addition, we demonstrate a novel all-optical stabilisation technique for mode-locked semiconductor lasers by combination of CW optical injection and optical feedback to simultaneously improve the time-bandwidth product and timing-jitter of the laser. This scheme does not need an RF source and no optical to electrical conversion is required and thus is ideal for photonic integration. Finally, an application of injection-locked mode-locked lasers is introduced in a multichannel phase-sensitive amplifier (PSA). We show that with dual-mode injection-locking, simultaneous phase-synchronisation of two channels to local pump sources is realised through one injection-locking stage. An experimental proof of concept is demonstrated for two 10 Gbps phase-encoded (DPSK) channels showing more than 7 dB phase-sensitive gain and less than 1 dB penalty of the receiver sensitivity.

The role of glucocorticoid-induced tumour necrosis factor receptor in developing mouse sympathetic neurons

Hereditary sensory autonomic neuropathy IV (HSAN IV) is an autosomal recessive disorder characterised by inability to feel pain and anhidrosis and is a consequence of defective NGF/TrkA signalling and growth of sensory and sympathetic neurons. Glucocortiocoid-induced tumour necrosis factors receptor (GITR), a transmembrane protein, activated by its specific ligand, GITRL, is well known for its role in the regulation of innate and acquired immune system responses. Recently, GITR was found to be required for NGF-dependant and extracellular signal-related kinase 1/2 (ERK1/2)-induced neurite growth and target innervation in the developing sympathetic nervous system (SNS). Given this novel role of GITR, it is possible that strategies targeting GITR have potential therapeutic benefit in promoting neurite growth in autonomic neuropathies such as HSAN IV. Using P1 mouse SCG neurons as a model, in addition to various SCG cell treatments, knock down models and transfection methods, we investigated whether GITR increases the sensitivity of sympathetic neurons to NGF; the region of GITR required for the enhancement of NGF-promoted growth, the signalling pathways downstream of GITR and how extensively GITR is involved in regulating peripheral innervation of the SNS. Results indicate that the region responsible for the growth promoting effects of GITR lies in its juxtamembrane intracellular region (here termed the growth promoting domain (GPD)) of GITR. The GPD of GITR activates ERK1/2 and inhibits nuclear factor kappa B (NF-κB) in an inverse fashion to provide an optimal cellular growth environment for P1 SCG neurons. While deleting the GPD of GITR had no effect on TrkA expression, constitutive phosphorylation of specific sites in the GPD reduced TrkA expression indicating a possible role for GITR in increasing the sensitivity of SCG neurons to NGF by the regulation of these sites, TrkA expression and subsequent NGF/TrkA binding. GITR appears to be heterogeneously required for NGF-promoted target innervation of SCG neurons in some organs, implying additional factors are involved in extensive NGF-target innervation of the SNS. In conclusion, this study answers basic biological questions regarding the molecular mechanism behind the role of GITR in the development of the SNS, and provides a basis for future research if GITR modulation is to be developed as a strategy for promoting axonal growth.

Development and characterization of novel transgenic techniques for the study of neuronal circuitry

Modern neuroscience relies heavily on sophisticated tools that allow us to visualize and manipulate cells with precise spatial and temporal control. Transgenic mouse models, for example, can be used to manipulate cellular activity in order to draw conclusions about the molecular events responsible for the development, maintenance and refinement of healthy and/or diseased neuronal circuits. Although it is fairly well established that circuits respond to activity-dependent competition between neurons, we have yet to understand either the mechanisms underlying these events or the higher-order plasticity that synchronizes entire circuits. In this thesis we aimed to develop and characterize transgenic mouse models that can be used to directly address these outstanding biological questions in different ways. We present SLICK-H, a Cre-expressing mouse line that can achieve drug-inducible, widespread, neuron-specific manipulations in vivo. This model is a clear improvement over existing models because of its particularly strong, widespread, and even distribution pattern that can be tightly controlled in the absence of drug induction. We also present SLICK-V::Ptox, a mouse line that, through expression of the tetanus toxin light chain, allows long-term inhibition of neurotransmission in a small subset (<1%) of fluorescently labeled pyramidal cells. This model, which can be used to study how a silenced cell performs in a wildtype environment, greatly facilitates the in vivo study of activity-dependent competition in the mammalian brain. As an initial application we used this model to show that tetanus toxin-expressing CA1 neurons experience a 15% - 19% decrease in apical dendritic spine density. Finally, we also describe the attempt to create additional Cre-driven mouse lines that would allow conditional alteration of neuronal activity either by hyperpolarization or inhibition of neurotransmission. Overall, the models characterized in this thesis expand upon the wealth of tools available that aim to dissect neuronal circuitry by genetically manipulating neurons in vivo.

The expression and regulation of pregnancy-specific glycoproteins in the mouse

Pregnancy-Specific Glycoproteins (PSG) are the most abundant fetally expressed proteins in the maternal bloodstream at term. This multigene family are immunoglobulin superfamily members and are predominantly expressed in the syncytiotrophoblast of human placenta and in giant cells and spongiotrophoblast of rodent placenta. PSGs are encoded by seventeen genes in the mouse and ten genes in the human. Little is known about the function of this gene family, although they have been implicated in immune modulation and angiogenesis through the induction of cytokines such as IL-10 and TGFβ1 in monocytes, and more recently, have been shown to inhibit the platelet-fibrinogen interaction. I provide new information concerning the evolution of the murine Psg genomic locus structure and organisation, through the discovery of a recent gene inversion event of Psg22 within the major murine Psg cluster. In addition to this, I have performed an examination of the expression patterns of individual Psg genes in placental and non-placental tissues. This study centres on Psg22, which is the most abundant murine Psg transcript detected in the first half of pregnancy. A novel alternative splice variant transcript of Psg22 lacking the protein N1-domain was discovered, and similar to the full length isoform induces TGFβ1 in macrophage and monocytic cell lines. The identification of a bidirectional antisense long non-coding RNA transcript directly adjacent to Psg22 and its associated active local chromatin conformation, suggests an interesting epigenetic gene-specific regulatory mechanism that may be responsible for the high level of Psg22 expression relative to the other Psg family members upon trophoblast giant cell differentiation

The role of the IL-1 type 1 receptor in the life, death and differentiation of adult hippocampal neural precursor cells

Neurogenesis occurs in two distinct regions of the adult brain; the subgranular zone (SGZ) of the dentate gyrus (DG) in the hippocampus, and the subventricular zone (SVZ) lining the lateral ventricles. It is now well-known that adult hippocampal neurogenesis can be modulated by a number of intrinsic and extrinsic factors e.g. local signalling molecules, exercise, environmental enrichment and learning. Moreover, levels of adult hippocampal neurogenesis decrease with age, at least in rodents, and alterations in hippocampal neurogenesis have been reported in animal models and human studies of neuropsychiatric and neurodegenerative conditions. Neuroinflammation is a common pathological feature of these conditions and is also a potent modulator of adult hippocampal neurogenesis. Recently, the orphan nuclear receptor TLX has been identified as an important regulator of adult hippocampal neurogenesis as its expression is necessary to maintain the neural precursor cell (NPC) pool in the adult DG. Likewise, exposure of animals to voluntary exercise has been consistently demonstrated to promote adult hippocampal neurogenesis. Lentivirus (LV)- mediated gene transfer is a useful tool to elucidate gene function and to explore potential therapeutic candidates across an array of conditions as it facilitates sustained gene expression in both dividing and post-mitotic cell populations. Both intrinsic and extrinsic factors are important regulators of adult hippocampal neurogenesis. Examining how these factors are affected by an inflammatory stimulus, and the subsequent effects on adult hippocampal neurogenesis provides important information for the development of novel treatment strategies for neuropsychiatric and neurodegenerative conditions in which adult hippocampal neurogenesis is impaired. The aims of the series of experiments presented in this thesis were to examine the effect of the pro-inflammatory cytokine interleukin-1β (IL-1β) on adult hippocampal NPCs both in vitro and in vivo. In vitro, we have shown that IL-1β reduces proliferation of adult hippocampal NPCs in a dose and time-dependent manner. In addition, we have demonstrated that TLX expression is reduced by IL-1β. Blockade of IL-1β signalling prevented both the IL-1β-induced reduction in cell proliferation and TLX expression. In vivo, we examined the effect of short term and long term exposure to LV-IL-1β in sedentary mice and in mice exposed to voluntary running. We demonstrated that impaired hippocampal neurogenesis is only evident after long term exposure to IL-1β. In mice exposed to voluntary running, hippocampal neurogenesis is significantly increased following short-term but not long-term exposure to running. Moreover, short-term running effectively prevents any IL-1β-induced effects on hippocampal neurogenesis; however, no such effects are seen following long-term exposure to running.

Secure architectures for pairing based public key cryptography

Along with the growing demand for cryptosystems in systems ranging from large servers to mobile devices, suitable cryptogrophic protocols for use under certain constraints are becoming more and more important. Constraints such as calculation time, area, efficiency and security, must be considered by the designer. Elliptic curves, since their introduction to public key cryptography in 1985 have challenged established public key and signature generation schemes such as RSA, offering more security per bit. Amongst Elliptic curve based systems, pairing based cryptographies are thoroughly researched and can be used in many public key protocols such as identity based schemes. For hardware implementions of pairing based protocols, all components which calculate operations over Elliptic curves can be considered. Designers of the pairing algorithms must choose calculation blocks and arrange the basic operations carefully so that the implementation can meet the constraints of time and hardware resource area. This thesis deals with different hardware architectures to accelerate the pairing based cryptosystems in the field of characteristic two. Using different top-level architectures the hardware efficiency of operations that run at different times is first considered in this thesis. Security is another important aspect of pairing based cryptography to be considered in practically Side Channel Analysis (SCA) attacks. The naively implemented hardware accelerators for pairing based cryptographies can be vulnerable when taking the physical analysis attacks into consideration. This thesis considered the weaknesses in pairing based public key cryptography and addresses the particular calculations in the systems that are insecure. In this case, countermeasures should be applied to protect the weak link of the implementation to improve and perfect the pairing based algorithms. Some important rules that the designers must obey to improve the security of the cryptosystems are proposed. According to these rules, three countermeasures that protect the pairing based cryptosystems against SCA attacks are applied. The implementations of the countermeasures are presented and their performances are investigated.

Dilute nitride semiconductors : band structure, scattering and high field transport

The substitution of a small fraction x of nitrogen atoms, for the group V elements in conventional III-V semiconductors such as GaAs and GaSb strongly perturbs the conduction band of the host semiconductor. In this thesis we investigate the effects of nitrogen states on the band dispersion, carrier scattering and mobility of dilute nitride alloys. In the supercell model we solve the single particle Hamiltonian for a very large supercell containing randomly placed nitrogen. This model predicts a gap in the density of states of GaNxAs1−x, where this gap is filled in the Green’s function model. Therefore we develop a self-consistent Green’s function (SCGF) approach, which provides excellent agreement with supercell calculations and reveals a gap in the DOS, in contrast with the results of previous non-self-consistent Green’s function calculations. However, including the distribution of N states destroys this gap, as seen in experiment. We then examine the high field transport of carriers by solving the steadystate Boltzmann transport equation and find that it is necessary to include the full distribution of N levels in order to account for the small, low-field mobility and the absence of a negative differential velocity regime observed experimentally with increasing x. Overall the results account well for a wide range of experimental data. We also investigate the band structure, scattering and mobility of carriers by finding the poles of the SCGF, which gives lower carrier mobility for GaNxAs1−x, compared to those already calculated, in better agreement with experiments. The calculated optical absorption spectra for InyGa1−yNxAs1−x and GaNxSb1−x using the SCGF agree well with the experimental data, confirming the validity of this approach to study the band structure of these materials.

Digital signal processing and artificial intelligence for the automated classification of food allergy

As a by-product of the ‘information revolution’ which is currently unfolding, lifetimes of man (and indeed computer) hours are being allocated for the automated and intelligent interpretation of data. This is particularly true in medical and clinical settings, where research into machine-assisted diagnosis of physiological conditions gains momentum daily. Of the conditions which have been addressed, however, automated classification of allergy has not been investigated, even though the numbers of allergic persons are rising, and undiagnosed allergies are most likely to elicit fatal consequences. On the basis of the observations of allergists who conduct oral food challenges (OFCs), activity-based analyses of allergy tests were performed. Algorithms were investigated and validated by a pilot study which verified that accelerometer-based inquiry of human movements is particularly well-suited for objective appraisal of activity. However, when these analyses were applied to OFCs, accelerometer-based investigations were found to provide very poor separation between allergic and non-allergic persons, and it was concluded that the avenues explored in this thesis are inadequate for the classification of allergy. Heart rate variability (HRV) analysis is known to provide very significant diagnostic information for many conditions. Owing to this, electrocardiograms (ECGs) were recorded during OFCs for the purpose of assessing the effect that allergy induces on HRV features. It was found that with appropriate analysis, excellent separation between allergic and nonallergic subjects can be obtained. These results were, however, obtained with manual QRS annotations, and these are not a viable methodology for real-time diagnostic applications. Even so, this was the first work which has categorically correlated changes in HRV features to the onset of allergic events, and manual annotations yield undeniable affirmation of this. Fostered by the successful results which were obtained with manual classifications, automatic QRS detection algorithms were investigated to facilitate the fully automated classification of allergy. The results which were obtained by this process are very promising. Most importantly, the work that is presented in this thesis did not obtain any false positive classifications. This is a most desirable result for OFC classification, as it allows complete confidence to be attributed to classifications of allergy. Furthermore, these results could be particularly advantageous in clinical settings, as machine-based classification can detect the onset of allergy which can allow for early termination of OFCs. Consequently, machine-based monitoring of OFCs has in this work been shown to possess the capacity to significantly and safely advance the current state of clinical art of allergy diagnosis

Theory of elasticity and electric polarization effects in the group-III nitrides

In this work, the properties of strained tetrahedrally bonded materials are explored theoretically, with special focus on group-III nitrides. In order to do so, a multiscale approach is taken: accurate quantitative calculations of material properties are carried out in a quantum first-principles frame, for small systems. These properties are then extrapolated and empirical methods are employed to make predictions for larger systems, such as alloys or nanostructures. We focus our attention on elasticity and electric polarization in semiconductors. These quantities serve as input for the calculation of the optoelectronic properties of these systems. Regarding the methods employed, our first-principles calculations use highly- accurate density functional theory (DFT) within both standard Kohn-Sham and generalized (hybrid functional) Kohn-Sham approaches. We have developed our own empirical methods, including valence force field (VFF) and a point-dipole model for the calculation of local polarization and local polarization potential. Our local polarization model gives insight for the first time to local fluctuations of the electric polarization at an atomistic level. At the continuum level, we have studied composition-engineering optimization of nitride nanostructures for built-in electrostatic field reduction, and have developed a highly efficient hybrid analytical-numerical staggered-grid computational implementation of continuum elasticity theory, that is used to treat larger systems, such as quantum dots.

Practical programming for static average-case analysis: the MOQA investigation

This work considers the static calculation of a program’s average-case time. The number of systems that currently tackle this research problem is quite small due to the difficulties inherent in average-case analysis. While each of these systems make a pertinent contribution, and are individually discussed in this work, only one of them forms the basis of this research. That particular system is known as MOQA. The MOQA system consists of the MOQA language and the MOQA static analysis tool. Its technique for statically determining average-case behaviour centres on maintaining strict control over both the data structure type and the labeling distribution. This research develops and evaluates the MOQA language implementation, and adds to the functions already available in this language. Furthermore, the theory that backs MOQA is generalised and the range of data structures for which the MOQA static analysis tool can determine average-case behaviour is increased. Also, some of the MOQA applications and extensions suggested in other works are logically examined here. For example, the accuracy of classifying the MOQA language as reversible is investigated, along with the feasibility of incorporating duplicate labels into the MOQA theory. Finally, the analyses that take place during the course of this research reveal some of the MOQA strengths and weaknesses. This thesis aims to be pragmatic when evaluating the current MOQA theory, the advancements set forth in the following work and the benefits of MOQA when compared to similar systems. Succinctly, this work’s significant expansion of the MOQA theory is accompanied by a realistic assessment of MOQA’s accomplishments and a serious deliberation of the opportunities available to MOQA in the future.