Impact of optical phase conjugation on the nonlinear Shannon limit

Compensation of the detrimental impacts of nonlinearity on long-haul wavelength division multiplexed system performance is discussed, and the difference between transmitter, receiver and in-line compensation analyzed. We demonstrate that ideal compensation of nonlinear noise could result in an increase in the signal-to-noise ratio (measured in dB) of 50%, and that reaches may be more than doubled for higher order modulation formats. The influence of parametric noise amplification is discussed in detail, showing how increased numbers of optical phase conjugators may further increase the received signal-tonoise ratio. Finally the impact of practical real world system imperfections, such as polarization mode dispersion, are outlined.

Dynamics of the Disk-Pendulum Coupled System With Vertical Excitation

This paper investigates the static and dynamic characteristics of the semi-elliptical rocking disk on which a pendulum pinned. This coupled system’s response is also analyzed analytically and numerically when a vertical harmonic excitation is applied to the bottom of the rocking disk. Lagrange’s Equation is used to derive the motion equations of the disk-pendulum coupled system. The second derivative test for the system’s potential energy shows how the location of the pendulum’s pivotal point affects the number and stability of equilibria, and the change of location presents different bifurcation diagrams for different geometries of the rocking disk. For both vertically excited and unforced cases, the coupled system shows chaos easily, but the proper chosen parameters can still help the system reach and keep the steady state. For the steady state of the vertically excited rocking disk without a pendulum, the variation of the excitation’s amplitude and frequency result in the hysteresis for the amplitude of the response. When a pendulum is pinned on the rocking disk, three major categories of steady states are presently in the numerical way.

Nonlinear optics with cold Rb atoms using tapered optical nanofibres

Optical nanofibres (ONFs) are very thin optical waveguides with sub-wavelength diameters. ONFs have very high evanescent fields and the guided light is confined strongly in the transverse direction. These fibres can be used to achieve strong light-matter interactions. Atoms around the waist of an ONF can be probed by collecting the atomic fluorescence coupling or by measuring the transmission (or the polarisation) of the probe beam sent through it. This thesis presents experiments using ONFs for probing and manipulating laser-cooled 87Rb atoms. As an initial experiment, a single mode ONF was integrated into a magneto-optical trap (MOT) and used for measuring the characteristics of the MOT, such as the loading time and the average temperature of the atom cloud. The effect of a near-resonant probe beam on the local temperature of the cold atoms has been studied. Next, the ONF was used for manipulating the atoms in the evanescent fields region in order to generate nonlinear optical effects. Four-wave mixing, ac Stark effect (Autler-Townes splitting) and electromagnetically induced transparency have been observed at unprecedented ultralow power levels. In another experiment, a few-mode ONF, supporting only the fundamental mode and the first higher order mode group, has been used for studying cold atoms. A higher pumping rate of the atomic fluorescence into the higher order fibreguided modes and more interactions with the surrounding atoms for higher order mode evanescent light, when compared to signals for the fundamental mode, have been identified. The results obtained in the thesis are particularly for a fundamental understanding of light-atom interactions when atoms are near a dielectric surface and also for the development of fibre-based quantum information technologies. Atoms coupled to ONFs could be used for preparing intrinsically fibre-coupled quantum nodes for quantum computing and the studies presented here are significant for a detailed understanding of such a system.

Complete framework for efficient characterisation of non-Markovian processes

A non-Markovian process is one that retains `memory' of its past. A systematic understanding of these processes is necessary to fully describe and harness a vast range of complex phenomena; however, no such general characterisation currently exists. This long-standing problem has hindered advances in understanding physical, chemical and biological processes, where often dubious theoretical assumptions are made to render a dynamical description tractable. Moreover, the methods currently available to treat non-Markovian quantum dynamics are plagued with unphysical results, like non-positive dynamics. Here we develop an operational framework to characterise arbitrary non-Markovian quantum processes. We demonstrate the universality of our framework and how the characterisation can be rendered efficient, before formulating a necessary and sufficient condition for quantum Markov processes. Finally, we stress how our framework enables the actual systematic analysis of non-Markovian processes, the understanding of their typicality, and the development of new master equations for the effective description of memory-bearing open-system evolution.

Characterisation of Large Disturbance Rotor Angle and Voltage Stability in Interconnected Power Networks with Distributed Wind Generation

Wind generation in highly interconnected power networks creates local and centralised stability issues based on their proximity to conventional synchronous generators and load centres. This paper examines the large disturbance stability issues (i.e. rotor angle and voltage stability) in power networks with geographically distributed wind resources in the context of a number of dispatch scenarios based on profiles of historical wind generation for a real power network. Stability issues have been analysed using novel stability indices developed from dynamic characteristics of wind generation. The results of this study show that localised stability issues worsen when significant penetration of both conventional and wind generation is present due to their non-complementary characteristics. In contrast, network stability improves when either high penetration of wind and synchronous generation is present in the network. Therefore, network regions can be clustered into two distinct stability groups (i.e. superior stability and inferior stability regions). Network stability improves when a voltage control strategy is implemented at wind farms, however both stability clusters remain unchanged irrespective of change in the control strategy. Moreover, this study has shown that the enhanced fault ride-through (FRT) strategy for wind farms can improve both voltage and rotor angle stability locally, but only a marginal improvement is evident in neighbouring regions.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Characterisation of polyethylene powders for rotational moulding and effect of powder size and shape on densification behaviour

The particle size, shape and distribution of a range of rotational moulding polyethylenes (PEs) ground to powder was investigated using a novel visual data acquisition and analysis system (TP Picture®), developed by Total Petrochemicals. Differences in the individual particle shape factors of the powder samples were observed and correlations with the grinding conditions were determined. When heated, the bubble dissolution behaviour of the same powders was investigated and the shape factor correlated with densification rate, bubble size and bubble distribution.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Filamentation in Air and Water and Nonlinear Optical Characterization of Biopolymer Using Ultrashort Laser Pulses

Important issues related to femtosecond (fs) pulses and its relevance to this thesis are discussed. A fundamental characteristic, like the timebandwidth product for fs pulses is decribed in detail. A brief review of generation of ultrashort pulses and its propagation through an optically transparent media are presented. Interaction of strong pulses with matter and different ionization processes are also described. An overview of the thesis is presented at the end

Model order reduction for parameterized nonlinear evolution equations

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

A 3D printed electromagnetic nonlinear vibration energy harvester

A 3D printed electromagnetic vibration energy harvester is presented. The motion of the device is in-plane with the excitation vibrations, and this is enabled through the exploitation of a leaf isosceles trapezoidal flexural pivot topology. This topology is ideally suited for systems requiring restricted out-of-plane motion and benefits from being fabricated monolithically. This is achieved by 3D printing the topology with materials having a low flexural modulus. The presented system has a nonlinear softening spring response, as a result of designed magnetic force interactions. A discussion of fatigue performance is presented and it is suggested that whilst fabricating, the raster of the suspension element is printed perpendicular to the flexural direction and that the experienced stress is as low as possible during operation, to ensure longevity. A demonstrated power of ~25 μW at 0.1 g is achieved and 2.9 mW is demonstrated at 1 g. The corresponding bandwidths reach up-to 4.5 Hz. The system's corresponding power density of ~0.48 mW cm−3 and normalised power integral density of 11.9 kg m−3 (at 1 g) are comparable to other in-plane systems found in the literature.

Temperature regulation of a pilot-scale batch reaction system via explicit model predictive control

In this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy -- Some mathematical models are developed from experimental data to describe the system behavior -- The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed -- The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework

Generation and Characterisation of a Canine EGFP-HMGA2 Prostate Cancer In Vitro Model

The architectural transcription factor HMGA2 is abundantly expressed during embryonic development. In several malignant neoplasias including prostate cancer, high re-expression of HMGA2 is correlated with malignancy and poor prognosis. The let-7 miRNA family is described to regulate HMGA2 negatively. The balance of let-7 and HMGA2 is discussed to play a major role in tumour aetiology. To further analyse the role of HMGA2 in prostate cancer a stable and highly reproducible in vitro model system is precondition. Herein we established a canine CT1258-EGFP-HMGA2 prostate cancer cell line stably overexpressing HMGA2 linked to EGFP and in addition the reference cell line CT1258-EGFP expressing solely EGFP to exclude EGFP-induced effects. Both recombinant cell lines were characterised by fluorescence microscopy, flow cytometry and immunocytochemistry. The proliferative effect of ectopically overexpressed HMGA2 was determined via BrdU assays. Comparative karyotyping of the derived and the initial CT1258 cell lines was performed to analyse chromosome consistency. The impact of the ectopic HMGA2 expression on its regulator let-7a was analysed by quantitative real-time PCR. Fluorescence microscopy and immunocytochemistry detected successful expression of the EGFP-HMGA2 fusion protein exclusively accumulating in the nucleus. Gene expression analyses confirmed HMGA2 overexpression in CT1258-EGFP-HMGA2 in comparison to CT1258-EGFP and native cells. Significantly higher let-7a expression levels were found in CT1258-EGFP-HMGA2 and CT1258-EGFP. The BrdU assays detected an increased proliferation of CT1258-HMGA2-EGFP cells compared to CT1258-EGFP and native CT1258. The cytogenetic analyses of CT1258-EGFP and CT1258-EGFP-HMGA2 resulted in a comparable hyperdiploid karyotype as described for native CT1258 cells. To further investigate the impact of recombinant overexpressed HMGA2 on CT1258 cells, other selected targets described to underlie HMGA2 regulation were screened in addition. The new fluorescent CT1258-EGFP-HMGA2 cell line is a stable tool enabling in vitro and in vivo analyses of the HMGA2-mediated effects on cells and the development and pathogenesis of prostate cancer.

Molecular and biological characterisation of orthobunyaviruses

Orthobunyaviruses are the largest genus within the Bunyaviridae family, with over 170 named viruses classified into 18 serogroups (Elliott and Blakqori, 2001; Plyusnin et al., 2012). Orthobunyaviruses are transmitted by arthropods and have a tripartite negative sense RNA genome, which encodes 4 structural proteins and 2 non-structural proteins. The non-structural protein NSs is the primary virulence factor of orthobunyaviruses and potent antagonist of the type I interferon (IFN) response. However, sequencing studies have identified pathogenic viruses that lack the NSs protein (Mohamed et al., 2009; Gauci et al., 2010). The work presented in this thesis describes the molecular and biological characterisation of divergent orthobunyaviruses. Data on plaque morphology, growth kinetics, protein profiles, sensitivity to IFN and activation of the type I IFN system are presented for viruses in the Anopheles A, Anopheles B, Capim, Gamboa, Guama, Minatitlan, Nyando, Tete and Turlock serogroups. These are complemented with complete genome sequencing and phylogenetic analysis. Low activation of IFN by Tete serogroup viruses, which naturally lack an NSs protein, was also further investigated by the development of a reverse genetics system for Batama virus (BMAV). Recombinant viruses with mutations in the virus nucleocapsid protein amino terminus showed higher activation of type I IFN in vitro and data suggests that low levels of IFN are due to lower activation rather than active antagonism. The anti-orthobunyavirus activity of IFN-stimulated genes IFI44, IFITMs and human and ovine BST2 were also studied, revealing that activity varies not only within the orthobunyavirus genus and virus serogroups but also within virus species. Furthermore, there was evidence of active antagonism of the type I IFN response and ISGs by non-NSs viruses. In summary, the results show that pathogenicity in man and antagonism of the type I IFN response in vitro cannot be predicted by the presence, or absence, of an NSs ORF. They also highlight problems in orthobunyavirus classification with discordance between classical antigen based data and phylogenetic analysis.

Nonlinear periodic problems with a jumping reaction

We consider a periodic problem driven by the scalar $p-$Laplacian and with a jumping (asymmetric) reaction. We prove two multiplicity theorems. The first concerns the nonlinear problem ($1