Analysis and optimisation of semiconductor reflective modulators for optical networks

Reflective modulators based on the combination of an electroabsorption modulator (EAM) and semiconductor optical amplifier (SOA) are attractive devices for applications in long reach carrier distributed passive optical networks (PONs) due to the gain provided by the SOA and the high speed and low chirp modulation of the EAM. Integrated R-EAM-SOAs have experimentally shown two unexpected and unintuitive characteristics which are not observed in a single pass transmission SOA: the clamping of the output power of the device around a maximum value and low patterning distortion despite the SOA being in a regime of gain saturation. In this thesis a detailed analysis is carried out using both experimental measurements and modelling in order to understand these phenomena. For the first time it is shown that both the internal loss between SOA and R-EAM and the SOA gain play an integral role in the behaviour of gain saturated R-EAM-SOAs. Internal loss and SOA gain are also optimised for use in a carrier distributed PONs in order to access both the positive effect of output power clamping, and hence upstream dynamic range reduction, combined with low patterning operation of the SOA Reflective concepts are also gaining interest for metro transport networks and short reach, high bit rate, inter-datacentre links. Moving the optical carrier generation away from the transmitter also has potential advantages for these applications as it avoids the need for cooled photonics being placed directly on hot router line-cards. A detailed analysis is carried out in this thesis on a novel colourless reflective duobinary modulator, which would enable wavelength flexibility in a power-efficient reflective metro node.

Effect of peak inert-mode temperature on elemental carbon measured using thermal-optical analysis

Thermal-optical analysis is a conventional method for classifying carbonaceous aerosols as organic carbon (OC) and elemental carbon (EC). This article examines the effects of three different temperature protocols on the measured EC. For analyses of parallel punches from the same ambient sample, the protocol with the highest peak helium-mode temperature (870°C) gives the smallest amount of EC, while the protocol with the lowest peak helium-mode temperature (550°C) gives the largest amount of EC. These differences are observed when either sample transmission or reflectance is used to define the OC/EC split. An important issue is the effect of the peak helium-mode temperature on the relative rate at which different types of carbon with different optical properties evolve from the filter. Analyses of solvent-extracted samples are used to demonstrate that high temperatures (870°C) lead to premature EC evolution in the helium-mode. For samples collected in Pittsburgh, this causes the measured EC to be biased low because the attenuation coefficient of pyrolyzed carbon is consistently higher than that of EC. While this problem can be avoided by lowering the peak helium-mode temperature, analyses of wood smoke dominated ambient samples and levoglucosan-spiked filters indicate that too low helium-mode peak temperatures (550°C) allow non-light absorbing carbon to slip into the oxidizing mode of the analysis. If this carbon evolves after the OC/EC split, it biases the EC measurements high. Given the complexity of ambient aerosols, there is unlikely to be a single peak helium-mode temperature at which both of these biases can be avoided. Copyright © American Association for Aerosol Research.

Fostering 'habits of reflection, independent study and free inquiry': an analysis of the short-lived phenomenon of General/Liberal Studies in English vocational education and training

In 1957, 12 years after the end of World War II, the Ministry of Education issued Circular 323 to promote the development of an element of ‘liberal studies’ in courses offered by technical and further education (FE) colleges in England. This was perceived to be in some ways a peculiar or uncharacteristic development. However, it lasted over 20 years, during which time most students on courses in FE colleges participated in what were termed General or Liberal Studies classes that complemented and/or contrasted with the technical content of their vocational programmes. By the end of the 1970s, these classes had changed in character, moving away from the concept of a ‘liberal education’ towards a prescribed diet of ‘communication studies’. The steady decline in apprenticeship numbers from the late 1960s onwards accelerated in the late 1970s, resulting in a new type of student (the state-funded ‘trainee’) into colleges whose curriculum would be prescribed by the Manpower Services Commission. This paper examines the Ministry’s thinking and charts the rise and fall of a curriculum phenomenon that became immortalised in the ‘Wilt’ novels of Tom Sharpe. The paper argues that the Ministry of Education’s concerns half a century ago are still relevant now, particularly as fresh calls are being made to raise the leaving age from compulsory education to 18, and in light of attempts in England to develop new vocational diplomas for full-time students in schools and colleges.

A Tunable Split Resonator Method for Non-destructive Permittivity Characterization

The split cylinder resonator method is improved for nondestructive and accurate measurement for low permittivity materials at multiple frequency points. The dielectric constants of flat substrate materials are calculated based on a rigorous mode match analysis of the TE/sub 011/ mode. The loss tangent is also approximately calculated. The dielectric properties of two commercial substrates have been measured at multiple frequencies. The results demonstrate that this technology is capable of accurately characterizing the dielectric properties of flat substrate materials versus frequency in a nondestructive way.

Development of sampling methods for Raman analysis of solid dosage forms of therapeutic and illicit drugs

The results of a study aimed at determining the most important experimental parameters for automated, quantitative analysis of solid dosage form pharmaceuticals (seized and model 'ecstasy' tablets) are reported. Data obtained with a macro-Raman spectrometer were complemented by micro-Raman measurements, which gave information on particle size and provided excellent data for developing statistical models of the sampling errors associated with collecting data as a series of grid points on the tablets' surface. Spectra recorded at single points on the surface of seized MDMA-caffeine-lactose tablets with a Raman microscope (lambda(ex) = 785 nm, 3 mum diameter spot) were typically dominated by one or other of the three components, consistent with Raman mapping data which showed the drug and caffeine microcrystals were ca 40 mum in diameter. Spectra collected with a microscope from eight points on a 200 mum grid were combined and in the resultant spectra the average value of the Raman band intensity ratio used to quantify the MDMA: caffeine ratio, mu(r), was 1.19 with an unacceptably high standard deviation, sigma(r), of 1.20. In contrast, with a conventional macro-Raman system (150 mum spot diameter), combined eight grid point data gave mu(r) = 1.47 with sigma(r) = 0.16. A simple statistical model which could be used to predict sigma(r) under the various conditions used was developed. The model showed that the decrease in sigma(r) on moving to a 150 mum spot was too large to be due entirely to the increased spot diameter but was consistent with the increased sampling volume that arose from a combination of the larger spot size and depth of focus in the macroscopic system. With the macro-Raman system, combining 64 grid points (0.5 mm spacing and 1-2 s accumulation per point) to give a single averaged spectrum for a tablet was found to be a practical balance between minimizing sampling errors and keeping overhead times at an acceptable level. The effectiveness of this sampling strategy was also tested by quantitative analysis of a set of model ecstasy tablets prepared from MDEA-sorbitol (0-30% by mass MDEA). A simple univariate calibration model of averaged 64 point data had R-2 = 0.998 and an r.m.s. standard error of prediction of 1.1% whereas data obtained by sampling just four points on the same tablet showed deviations from the calibration of up to 5%.

Process monitoring approach using fast moving window PCA

This paper introduces a fast algorithm for moving window principal component analysis (MWPCA) which will adapt a principal component model. This incorporates the concept of recursive adaptation within a moving window to (i) adapt the mean and variance of the process variables, (ii) adapt the correlation matrix, and (iii) adjust the PCA model by recomputing the decomposition. This paper shows that the new algorithm is computationally faster than conventional moving window techniques, if the window size exceeds 3 times the number of variables, and is not affected by the window size. A further contribution is the introduction of an N-step-ahead horizon into the process monitoring. This implies that the PCA model, identified N-steps earlier, is used to analyze the current observation. For monitoring complex chemical systems, this work shows that the use of the horizon improves the ability to detect slowly developing drifts.

Forensic analysis of architectural finishes using Fourier transform infrared and Raman spectroscopy, Part I: The resin bases

The ability of Raman spectroscopy and Fourier transform infrared (FT-IR) microscopy to discriminate between resins used for the manufacture of architectural finishes was examined in a study of 39 samples taken from a commercial resin library. Both Raman and FT-IR were able to discriminate between different types of resin and both split the samples into several groups (six for FT-IR, six for Raman), each of which gave similar, but not identical, spectra. In addition, three resins gave unique Raman spectra (four in FTIR). However, approximately half the library comprised samples that were sufficiently similar that they fell into a single large group, whether classified using FT-IR or Raman, although the remaining samples fell into much smaller groups. Further sub-division of the FT-IR groups was not possible because the experimental uncertainty was of similar magnitude to the within-group variation. In contrast, Raman spectroscopy was able to further discriminate between resins that fell within the same groups because the differences in the relative band intensities of the resins, although small, were larger than the experimental uncertainty.

Exploratory analysis of spatiotemporal patterns of cellular automata by clustering compressibility

In this paper we study the classification of spatiotemporal pattern of one-dimensional cellular automata (CA) whereas the classification comprises CA rules including their initial conditions. We propose an exploratory analysis method based on the normalized compression distance (NCD) of spatiotemporal patterns which is used as dissimilarity measure for a hierarchical clustering. Our approach is different with respect to the following points. First, the classification of spatiotemporal pattern is comparative because the NCD evaluates explicitly the difference of compressibility among two objects, e.g., strings corresponding to spatiotemporal patterns. This is in contrast to all other measures applied so far in a similar context because they are essentially univariate. Second, Kolmogorov complexity, which underlies the NCD, was used in the classification of CA with respect to their spatiotemporal pattern. Third, our method is semiautomatic allowing us to investigate hundreds or thousands of CA rules or initial conditions simultaneously to gain insights into their organizational structure. Our numerical results are not only plausible confirming previous classification attempts but also shed light on the intricate influence of random initial conditions on the classification results.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Meta analysis of the effects of lithium usage on serum creatinine levels

There is conflicting evidence concerning lithium’s effect on renal function. The aim is to clarify whether lithium affects kidney function and at what stage of treatment any effect may occur. Systematic review identified 23 studies split into three groups on which meta-analysis was performed to identify the following: A) lithium’s effect on renal function in cross-sectional case-control studies, B) studies of renal function before and after commencement on lithium, C) studies of longer term effect in those already established on lithium therapy. Group A showed a statistically significant increase of 5.7 µmol/L in creatinine in the study population compared with controls. Group B showed a non-statistically significant rise in creatinine (2.9 µmol/L) after a mean follow-up of 86 months. Group C showed a statistically significant increase in creatinine of 7.0 µmol/L over a mean duration of 64 months. An increase in creatinine of an average of 1.6 µmol/L/year on lithium was also identified in this group. Any lithium-associated increase in serum creatinine is quantitatively small and of questionable clinical significance. However, routine renal function monitoring of patients on lithium is essential.

Drivers of sales performance: a contemporary meta-analysis. Have salespeople become knowledge brokers?

It has been 25 years since the publication of a comprehensive review of the full spectrum of salesperformance drivers. This study takes stock of the contemporary field and synthesizes empirical evidence from the period 1982–2008. The authors revise the classification scheme for sales performance determinants devised by Walker et al. (1977) and estimate both the predictive validity of its sub-categories and the impact of a range of moderators on determinant-sales performance relationships. Based on multivariate causal model analysis, the results make two major observations: (1) Five sub-categories demonstrate significant relationships with sales performance: selling-related knowledge (ß=.28), degree of adaptiveness (ß=.27), role ambiguity (ß=-.25), cognitive aptitude (ß=.23) and work engagement (ß=.23). (2) These sub-categories are moderated by measurement method, research context, and salestype variables. The authors identify managerial implications of the results and offer suggestions for further research, including the conjecture that as the world is moving toward a knowledge-intensive economy, salespeople could be functioning as knowledge-brokers. The results seem to back this supposition and indicate how it might inspire future research in the field of personal selling.

A Robust Curve-Fitting Procedure for the Analysis of Plasmid DNA Strand Break Data from Gel Electrophoresis

A robust method for fitting to the results of gel electrophoresis assays of damage to plasmid DNA caused by radiation is presented. This method makes use of nonlinear regression to fit analytically derived dose response curves to observations of the supercoiled, open circular and linear plasmid forms simultaneously, allowing for more accurate results than fitting to individual forms. Comparisons with a commonly used analysis method show that while there is a relatively small benefit between the methods for data sets with small errors, the parameters generated by this method remain much more closely distributed around the true value in the face of increasing measurement uncertainties. This allows for parameters to be specified with greater confidence, reflected in a reduction of errors on fitted parameters. On test data sets, fitted uncertainties were reduced by 30%, similar to the improvement that would be offered by moving from triplicate to fivefold repeats (assuming standard errors). This method has been implemented in a popular spreadsheet package and made available online to improve its accessibility. (C) 2011 by Radiation Research Society

Change in UK construction: Moving towards supply chain collaboration

There has been an increasing highlight of supply chain collaboration in UK construction. However, few studies have provided evidence for the current status. Based on the analysis of over 100 questionnaire responses in this research, it is found that the UK construction industry as a whole is experiencing an important change and moving towards supply chain collaboration. On the other hand, an unbalance is found for the change movement. In addition to the questionnaire survey, a series of expert interviews help to explore the specific characteristics of supply chain collaboration in construction and provide practical implications for collaboration strategy implementation.

Vulnerability and multiple deprivation perspectives on economic exclusion in Europe: A latent class analysis

In this paper we address issues relating to vulnerability to economic exclusion and levels of economic exclusion in Europe. We do so by applying latent class models to data from the European Community Household Panel for thirteen countries. This approach allows us to distinguish between vulnerability to economic exclusion and exposure to multiple deprivation at a particular point in time. The results of our analysis confirm that in every country it is possible to distinguish between a vulnerable and a non-vulnerable class. Association between income poverty, life-style deprivation and subjective economic strain is accounted for by allocating individuals to the categories of this latent variable. The size of the vulnerable class varies across countries in line with expectations derived from welfare regime theory. Between class differentiation is weakest in social democratic regimes but otherwise the pattern of differentiation is remarkably similar. The key discriminatory factor is life-style deprivation, followed by income and economic strain. Social class and employment status are powerful predictors of latent class membership in all countries but the strength of these relationships varies across welfare regimes. Individual biography and life events are also related to vulnerability to economic exclusion. However, there is no evidence that they account for any significant part of the socio-economic structuring of vulnerability and no support is found for the hypothesis that social exclusion has come to transcend class boundaries and become a matter of individual biography. However, the extent of socio-economic structuring does vary substantially across welfare regimes. Levels of economic exclusion, in the sense of current exposure to multiple deprivation, also vary systematically by welfare regime and social class. Taking both vulnerability to economic exclusion and levels of exclusion into account suggests that care should be exercised in moving from evidence on the dynamic nature of poverty and economic exclusion to arguments relating to the superiority of selective over universal social policies.

Relative role of deterministic and stochastic determinants of soil animal community: a spatially explicit analysis of oribatid mites

1. Ecologists are debating the relative role of deterministic and stochastic determinants of community structure. Although the high diversity and strong spatial structure of soil animal assemblages could provide ecologists with an ideal ecological scenario, surprisingly little information is available on these assemblages.
2. We studied species-rich soil oribatid mite assemblages from a Mediterranean beech forest and a grassland. We applied multivariate regression approaches and analysed spatial autocorrelation at multiple spatial scales using Moran's eigenvectors. Results were used to partition community variance in terms of the amount of variation uniquely accounted for by environmental correlates (e.g. organic matter) and geographical position. Estimated neutral diversity and immigration parameters were also applied to a soil animal group for the first time to simulate patterns of community dissimilarity expected under neutrality, thereby testing neutral predictions.
3. After accounting for spatial autocorrelation, the correlation between community structure and key environmental parameters disappeared: about 40% of community variation consisted of spatial patterns independent of measured environmental variables such as organic matter. Environmentally independent spatial patterns encompassed the entire range of scales accounted for by the sampling design (from tens of cm to 100 m). This spatial variation could be due to either unmeasured but spatially structured variables or stochastic drift mediated by dispersal. Observed levels of community dissimilarity were significantly different from those predicted by neutral models.
4. Oribatid mite assemblages are dominated by processes involving both deterministic and stochastic components and operating at multiple scales. Spatial patterns independent of the measured environmental variables are a prominent feature of the targeted assemblages, but patterns of community dissimilarity do not match neutral predictions. This suggests that either niche-mediated competition or environmental filtering or both are contributing to the core structure of the community. This study indicates new lines of investigation for understanding the mechanisms that determine the signature of the deterministic component of animal community assembly.