Use of a solvent-free dry matrix coating for quantitative matrix-assisted laser desorption ionization imaging of 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylate in rat brain and quantitative analysis of the drug from laser microdissected tissue regions

A dry matrix application for matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) was used to profile the distribution of 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylate, monohydrochloride (BDNC, SSR180711) in rat brain tissue sections. Matrix application involved applying layers of finely ground dry alpha-cyano-4-hydroxycinnamic acid (CHCA) to the surface of tissue sections thaw mounted onto MALDI targets. It was not possible to detect the drug when applying matrix in a standard aqueous-organic solvent solution. The drug was detected at higher concentrations in specific regions of the brain, particularly the white matter of the cerebellum. Pseudomultiple reaction monitoring imaging was used to validate that the observed distribution was the target compound. The semiquantitative data obtained from signal intensities in the imaging was confirmed by laser microdissection of specific regions of the brain directed by the imaging, followed by hydrophilic interaction chromatography in combination with a quantitative high-resolution mass spectrometry method. This study illustrates that a dry matrix coating is a valuable and complementary matrix application method for analysis of small polar drugs and metabolites that can be used for semiquantitative analysis.

Amplification of temporally modulated signal beams via two-wave mixing in Bi12SiO20

A theoretical analysis of two-wave mixing in a BSO crystal is developed in the undepleted-pump approximation for a modulated signal beam. It is shown that, for a modulation of high enough frequency, significant ac amplification is possible at three distinct values of pump-beam detuning. A signal beam that is amplitude modulated by a square wave is analyzed by means of the theory, and experimental results are presented in confirmation of the analysis. Finally, it is shown that in the presence of absorption the optimum detunings for dc and ac amplification are different.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

Numerical and statistical analysis of long-haul undersea optical communication systems

Firstly, we numerically model a practical 20 Gb/s undersea configuration employing the Return-to-Zero Differential Phase Shift Keying data format. The modelling is completed using the Split-Step Fourier Method to solve the Generalised Nonlinear Schrdinger Equation. We optimise the dispersion map and per-channel launch power of these channels and investigate how the choice of pre/post compensation can influence the performance. After obtaining these optimal configurations, we investigate the Bit Error Rate estimation of these systems and we see that estimation based on Gaussian electrical current systems is appropriate for systems of this type, indicating quasi-linear behaviour. The introduction of narrower pulses due to the deployment of quasi-linear transmission decreases the tolerance to chromatic dispersion and intra-channel nonlinearity. We used tools from Mathematical Statistics to study the behaviour of these channels in order to develop new methods to estimate Bit Error Rate. In the final section, we consider the estimation of Eye Closure Penalty, a popular measure of signal distortion. Using a numerical example and assuming the symmetry of eye closure, we see that we can simply estimate Eye Closure Penalty using Gaussian statistics. We also see that the statistics of the logical ones dominates the statistics of the logical ones dominates the statistics of signal distortion in the case of Return-to-Zero On-Off Keying configurations.

The application of parallel processing methods to vibrational analysis

The trend in modal extraction algorithms is to use all the available frequency response functions data to obtain a global estimate of the natural frequencies, damping ratio and mode shapes. Improvements in transducer and signal processing technology allow the simultaneous measurement of many hundreds of channels of response data. The quantity of data available and the complexity of the extraction algorithms make considerable demands on the available computer power and require a powerful computer or dedicated workstation to perform satisfactorily. An alternative to waiting for faster sequential processors is to implement the algorithm in parallel, for example on a network of Transputers. Parallel architectures are a cost effective means of increasing computational power, and a larger number of response channels would simply require more processors. This thesis considers how two typical modal extraction algorithms, the Rational Fraction Polynomial method and the Ibrahim Time Domain method, may be implemented on a network of transputers. The Rational Fraction Polynomial Method is a well known and robust frequency domain 'curve fitting' algorithm. The Ibrahim Time Domain method is an efficient algorithm that 'curve fits' in the time domain. This thesis reviews the algorithms, considers the problems involved in a parallel implementation, and shows how they were implemented on a real Transputer network.

Composite CDMA—a statistical mechanics analysis

Code division multiple access (CDMA) in which the spreading code assignment to users contains a random element has recently become a cornerstone of CDMA research. The random element in the construction is particularly attractive as it provides robustness and flexibility in utilizing multiaccess channels, whilst not making significant sacrifices in terms of transmission power. Random codes are generated from some ensemble; here we consider the possibility of combining two standard paradigms, sparsely and densely spread codes, in a single composite code ensemble. The composite code analysis includes a replica symmetric calculation of performance in the large system limit, and investigation of finite systems through a composite belief propagation algorithm. A variety of codes are examined with a focus on the high multi-access interference regime. We demonstrate scenarios both in the large size limit and for finite systems in which the composite code has typical performance exceeding those of sparse and dense codes at equivalent signal to noise ratio.

Time resolved bit error rate analysis of a fast switching tunable laser for use in optically switched networks

We investigate the use of different direct detection modulation formats in a wavelength switched optical network. We find the minimum time it takes a tunable sampled grating distributed Bragg reflector laser to recover after switching from one wavelength channel to another for different modulation formats. The recovery time is investigated utilizing a field programmable gate array which operates as a time resolved bit error rate detector. The detector offers 93 ps resolution operating at 10.7 Gb/s and allows for all the data received to contribute to the measurement, allowing low bit error rates to be measured at high speed. The recovery times for 10.7 Gb/s non-return-to-zero on–off keyed modulation, 10.7 Gb/s differentially phase shift keyed signal and 21.4 Gb/s differentially quadrature phase shift keyed formats can be as low as 4 ns, 7 ns and 40 ns, respectively. The time resolved phase noise associated with laser settling is simultaneously measured for 21.4 Gb/s differentially quadrature phase shift keyed data and it shows that the phase noise coupled with frequency error is the primary limitation on transmitting immediately after a laser switching event.

A peak-clustering method for MEG group analysis to minimise artefacts due to smoothness

Magnetoencephalography (MEG), a non-invasive technique for characterizing brain electrical activity, is gaining popularity as a tool for assessing group-level differences between experimental conditions. One method for assessing task-condition effects involves beamforming, where a weighted sum of field measurements is used to tune activity on a voxel-by-voxel basis. However, this method has been shown to produce inhomogeneous smoothness differences as a function of signal-to-noise across a volumetric image, which can then produce false positives at the group level. Here we describe a novel method for group-level analysis with MEG beamformer images that utilizes the peak locations within each participant's volumetric image to assess group-level effects. We compared our peak-clustering algorithm with SnPM using simulated data. We found that our method was immune to artefactual group effects that can arise as a result of inhomogeneous smoothness differences across a volumetric image. We also used our peak-clustering algorithm on experimental data and found that regions were identified that corresponded with task-related regions identified in the literature. These findings suggest that our technique is a robust method for group-level analysis with MEG beamformer images.

Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

Performance analysis of 20 Gb/s RZ-DPSK non-slope matched transoceanic submarine links

Direct computation of the bit-error rate (BER) and laboratory experiments are used to assess the performance of a non-slope matched transoceanic submarine transmission link operating at 20Gb/s channel rate and employing return-to-zero differential-phase shift keying (RZ-DPSK) signal modulation. Using this system as an example, we compare the accuracies of the existing theoretical approaches to the BER estimation for the RZ-DPSK format.

Evaluation of hemifield sector analysis protocol in multifocal visual evoked potential (MFVEP) objective perimetry for the diagnosis and early detection of glaucomatous field defects

Visual field assessment is a core component of glaucoma diagnosis and monitoring, and the Standard Automated Perimetry (SAP) test is considered up until this moment, the gold standard of visual field assessment. Although SAP is a subjective assessment and has many pitfalls, it is being constantly used in the diagnosis of visual field loss in glaucoma. Multifocal visual evoked potential (mfVEP) is a newly introduced method used for visual field assessment objectively. Several analysis protocols have been tested to identify early visual field losses in glaucoma patients using the mfVEP technique, some were successful in detection of field defects, which were comparable to the standard SAP visual field assessment, and others were not very informative and needed more adjustment and research work. In this study, we implemented a novel analysis approach and evaluated its validity and whether it could be used effectively for early detection of visual field defects in glaucoma. OBJECTIVES: The purpose of this study is to examine the effectiveness of a new analysis method in the Multi-Focal Visual Evoked Potential (mfVEP) when it is used for the objective assessment of the visual field in glaucoma patients, compared to the gold standard technique. METHODS: 3 groups were tested in this study; normal controls (38 eyes), glaucoma patients (36 eyes) and glaucoma suspect patients (38 eyes). All subjects had a two standard Humphrey visual field HFA test 24-2 and a single mfVEP test undertaken in one session. Analysis of the mfVEP results was done using the new analysis protocol; the Hemifield Sector Analysis HSA protocol. Analysis of the HFA was done using the standard grading system. RESULTS: Analysis of mfVEP results showed that there was a statistically significant difference between the 3 groups in the mean signal to noise ratio SNR (ANOVA p<0.001 with a 95% CI). The difference between superior and inferior hemispheres in all subjects were all statistically significant in the glaucoma patient group 11/11 sectors (t-test p<0.001), partially significant 5/11 (t-test p<0.01) and no statistical difference between most sectors in normal group (only 1/11 was significant) (t-test p<0.9). sensitivity and specificity of the HAS protocol in detecting glaucoma was 97% and 86% respectively, while for glaucoma suspect were 89% and 79%. DISCUSSION: The results showed that the new analysis protocol was able to confirm already existing field defects detected by standard HFA, was able to differentiate between the 3 study groups with a clear distinction between normal and patients with suspected glaucoma; however the distinction between normal and glaucoma patients was especially clear and significant. CONCLUSION: The new HSA protocol used in the mfVEP testing can be used to detect glaucomatous visual field defects in both glaucoma and glaucoma suspect patient. Using this protocol can provide information about focal visual field differences across the horizontal midline, which can be utilized to differentiate between glaucoma and normal subjects. Sensitivity and specificity of the mfVEP test showed very promising results and correlated with other anatomical changes in glaucoma field loss.

The role of hemifield sector analysis in multifocal visual evoked potential objective perimetry in the early detection of glaucomatous visual field defects

Objective: The purpose of this study was to examine the effectiveness of a new analysis method of mfVEP objective perimetry in the early detection of glaucomatous visual field defects compared to the gold standard technique. Methods and patients: Three groups were tested in this study; normal controls (38 eyes), glaucoma patients (36 eyes), and glaucoma suspect patients (38 eyes). All subjects underwent two standard 24-2 visual field tests: one with the Humphrey Field Analyzer and a single mfVEP test in one session. Analysis of the mfVEP results was carried out using the new analysis protocol: the hemifield sector analysis protocol. Results: Analysis of the mfVEP showed that the signal to noise ratio (SNR) difference between superior and inferior hemifields was statistically significant between the three groups (analysis of variance, P<0.001 with a 95% confidence interval, 2.82, 2.89 for normal group; 2.25, 2.29 for glaucoma suspect group; 1.67, 1.73 for glaucoma group). The difference between superior and inferior hemifield sectors and hemi-rings was statistically significant in 11/11 pair of sectors and hemi-rings in the glaucoma patients group (t-test P<0.001), statistically significant in 5/11 pairs of sectors and hemi-rings in the glaucoma suspect group (t-test P<0.01), and only 1/11 pair was statistically significant (t-test P<0.9). The sensitivity and specificity of the hemifield sector analysis protocol in detecting glaucoma was 97% and 86% respectively and 89% and 79% in glaucoma suspects. These results showed that the new analysis protocol was able to confirm existing visual field defects detected by standard perimetry, was able to differentiate between the three study groups with a clear distinction between normal patients and those with suspected glaucoma, and was able to detect early visual field changes not detected by standard perimetry. In addition, the distinction between normal and glaucoma patients was especially clear and significant using this analysis. Conclusion: The new hemifield sector analysis protocol used in mfVEP testing can be used to detect glaucomatous visual field defects in both glaucoma and glaucoma suspect patients. Using this protocol, it can provide information about focal visual field differences across the horizontal midline, which can be utilized to differentiate between glaucoma and normal subjects. The sensitivity and specificity of the mfVEP test showed very promising results and correlated with other anatomical changes in glaucomatous visual field loss. The intersector analysis protocol can detect early field changes not detected by the standard Humphrey Field Analyzer test. © 2013 Mousa et al, publisher and licensee Dove Medical Press Ltd.

Bit-error probability for direct detection of optical RZ signal degraded by ASE noise and timing jitter

We analyze theoretically the interplay between optical return-to-zero signal degradation due to timing jitter and additive amplified-spontaneous-emission noise. The impact of these two factors on the performance of a square-law direct detection receiver is also investigated. We derive an analytical expression for the bit-error probability and quantitatively determine the conditions when the contributions of the effects of timing jitter and additive noise to the bit error rate can be treated separately. The analysis of patterning effects is also presented. © 2007 IEEE.

A simulation of the surface EMG for analysis of muscle activity during whole body vibratory stimulation

Many studies have accounted for whole body vibration effects in the fields of exercise physiology, sport and rehabilitation medicine. Generally, surface EMG is utilized to assess muscular activity during the treatment; however, large motion artifacts appear superimposed to the raw signal, making sEMG recording not suitable before any artifact filtering. Sharp notch filters, centered at vibration frequency and at its superior harmonics, have been used in previous studies, to remove the artifacts. [6, 10] However, to get rid of those artifacts some true EMG signal is lost. The purpose of this study was to reproduce the effect of motor-unit synchronization on a simulated surface EMG during vibratory stimulation. In addition, authors mean to evaluate the EMG power percentage in those bands in which are also typically located motion artifact components. Model characteristics were defined to take into account two main aspect: the muscle MUs discharge behavior and the triggering effects that appear during local vibratory stimulation. [7] Inter-pulse-interval, was characterized by a polimodal distribution related to the MU discharge frequency (IPI 55-80ms, σ=12ms) and to the correlation with the vibration period within the range of ±2 ms due to vibration stimulus. [1, 7] The signals were simulated using different stimulation frequencies from 30 to 70 Hz. The percentage of the total simulated EMG power within narrow bands centered at the stimulation frequency and its superior harmonics (± 1 Hz) resulted on average about 8% (± 2.85) of the total EMG power. However, the artifact in those bands may contain more than 40% of the total power of the total signal. [6] Our preliminary results suggest that the analysis of the muscular activity of muscle based on raw sEMG recordings and RMS evaluation, if not processed during vibratory stimulation may lead to a serious overestimation of muscular response.

Signal processing using opto-electronic devices

All-optical signal processing is a powerful tool for the processing of communication signals and optical network applications have been routinely considered since the inception of optical communication. There are many successful optical devices deployed in today’s communication networks, including optical amplification, dispersion compensation, optical cross connects and reconfigurable add drop multiplexers. However, despite record breaking performance, all-optical signal processing devices have struggled to find a viable market niche. This has been mainly due to competition from electro-optic alternatives, either from detailed performance analysis or more usually due to the limited market opportunity for a mid-link device. For example a wavelength converter would compete with a reconfigured transponder which has an additional market as an actual transponder enabling significantly more economical development. Never-the-less, the potential performance of all-optical devices is enticing. Motivated by their prospects of eventual deployment, in this chapter we analyse the performance and energy consumption of digital coherent transponders, linear coherent repeaters and modulator based pulse shaping/frequency conversion, setting a benchmark for the proposed all-optical implementations.