Separation of VOCl3 from TiCl4 using soya oil

This thesis investigated the reactivity of the metal chlorides TiCl4, VOCl3 and VCl4 with different organic ligands. The chosen ligands were based around the chemical structure of soya oil due to its relevance to the industrial chlorine process used to manufacture TiO2. This thesis primarily used nuclear magnetic resonance (NMR)spectroscopy to characterise the reactions of the metal chlorides with soya oil and component parts, namely the glycerol and the alkene. This thesis goes on to investigate the coordination chemistry of the metal chlorides with ligands including diester groups. The chemical properties of the metal chlorides are known to be similar and hence hard to separate, the reactions studied provide a mechanism for their separation using diesters. It will be shown that TiCl4 coordinates with the ligands without the loss of any chlorine atoms and without disrupting the ligand. The VOCl3 reacted with the ligands, releasing a chlorine atom to produce a VOCl2 adduct. The difference in reactivity provides a removal mechanism. In the industrial process TiCl4 is present in very high concentrations and the coordination of TiCl4 can be seen as reversible and in equilibrium. Whereas, the VOCl3 converts VOCl3 into VOCl2, VOCl2 has a higher boiling point and can therefore be removed by distillation.

Synthesis and Characterisation of Various Diester and Triester Adducts of TiCl4

Titanium(IV) chloride and the triester glycerol tribenzoate (gtb) were reacted under moisture-free conditions in order to investigate the use of triester-containing oils in the purification of TiCl4 in industrial processes. This resulted in the isolation of a chloro-bridged dimeric complex containing four titanium centres [{(TiCl4)2(gtb)}2] (1). Further novel coordination compounds of TiCl4 and the diesters; diisopropyl malonate, dibenzyl malonate and diethyl succinate were synthesised by direct reaction under moisture-free conditions, yielding [TiCl4{CH2(COOiPr)2}] (2), [TiCl4{CH2(COOCH2Ph)2}] (3) and [TiCl4{C2H4(COOEt)2}] (4) respectively. The structures of compounds 1–4 were determined by single-crystal X-ray diffraction. All structures assumed an octahedral geometry consisting of the titanium bound to four chloride ligands and the diester molecule acting as a bidentate ligand, through its two carbonyl oxygen atoms. Exposure of the isopropyl malonate reaction to trace amounts of water during synthesis resulted in the formation of an oxo-bridged dimeric structure [Ti2(μ-O)Cl3{CH2(COOiPr)2}2] (2b), the structure of which was also obtained via single-crystal X-ray diffraction

Interferometric Techniques Using Embedded Optical Fibers for the Quantitative NDE of Composites

Optical interferometric techniques using single mode optical fiber waveguide embedded in composites and other layered materials have been used to measure one- and two-dimensional stress distributions and acoustic emission caused by applied point source loads. By interferometrically comparing the phases of coherent optical signals propagated through an embedded sample fiber and a bypass reference fiber, a signal proportional to the instantaneous strain integrated along the embedded length of the sample fiber has been detected. System calibration has been obtained by applying a one-dimensional dc strain field to a cantilever beam containing the fiber. Using this calibrated system, an array of fibers attached to a 15cm × 15cm x 0.3cm plate simply supported at the corners and subjected to point loading on the surface has been used to quantitatively determine the two-dimensional dc stress field in the plate. Finally, the calibrated ac response of the interferometer to acoustic emission events in a composite panel has been demonstrated. Potential applications are discussed

A Preference for a Sexual Signal Keeps Females Safe

Predation is generally thought to constrain sexual selection by female choice and limit the evolution of conspicuous sexual signals. Under high predation risk, females usually become less choosy, because they reduce their exposure to their predators by reducing the extent of their mate searching. However, predation need not weaken sexual selection if, under high predation risk, females exhibit stronger preferences for males that use conspicuous signals that help females avoid their predators. We tested this prediction in the fiddler crab Uca terpsichores by increasing females' perceived predation risk from crab-eating birds and measuring the attractiveness of a courtship signal that females use to find mates. The sexual signal is an arching mound of sand that males build at the openings of their burrows to which they attract females for mating. We found that the greater the risk, the more attractive were males with those structures. The benefits of mate preferences for sexual signals are usually thought to be linked to males' reproductive contributions to females or their young. Our study provides the first evidence that a female preference for a sexual signal can yield direct survival benefits by keeping females safe as they search for mates

Exploring differential item functioning in the SF-36 by demographic, clinical, psychological and social factors in an osteoarthritis population

The SF-36 is a very commonly used generic measure of health outcome in osteoarthritis (OA). An important, but frequently overlooked, aspect of validating health outcome measures is to establish if items work in the same way across subgroup of a population. That is, if respondents have the same 'true' level of outcome, does the item give the same score in different subgroups or is it biased towards one subgroup or another. Differential item functioning (DIF) can identify items that may be biased for one group or another and has been applied to measuring patient reported outcomes. Items may show DIF for different conditions and between cultures, however the SF-36 has not been specifically examined in an osteoarthritis population nor in a UK population. Hence, the aim of the study was to apply the DIF method to the SF-36 for a UK OA population. The sample comprised a community sample of 763 people with OA who participated in the Somerset and Avon Survey of Health. The SF-36 was explored for DIF with respect to demographic, social, clinical and psychological factors. Well developed ordinal regression models were used to identify DIF items. Results: DIF items were found by age (6 items), employment status (6 items), social class (2 items), mood (2 items), hip v knee (2 items), social deprivation (1 item) and body mass index (1 item). Although the impact of the DIF items rarely had a significant effect on the conclusions of group comparisons, in most cases there was a significant change in effect size. Overall, the SF-36 performed well with only a small number of DIF items identified, a reassuring finding in view of the frequent use of the SF-36 in OA. Nevertheless, where DIF items were identified it would be advisable to analyse data taking account of DIF items, especially when age effects are the focus of interest

Toward a Unified Genetic Map of Higher Plants, Transcending the Monocot-Dicot Divergence

Closely related (confamilial) genera often retain large chromosomal tracts in which gene order is colinear, punctuated by structural mutations such as inversions and translocations 1. To explore the possibility that conservation of gene order might extrapolate to more distantly related taxa, we first estimated an average structural mutation rate. Nine pairs of taxa, for which there exist both comparative genetic maps and plausible estimates of divergence time, showed an average of0.14 (±0.06) structural mutations per chromosome per million years of divergence (Myr; Table 1). This value is offered as a first approximation, acknowledging that refined comparative data and/or divergence estimates may impel revision

Exploring differential item functioning in the Western Ontario and McMaster Universities osteoarthritis index (WOMAC)

Background: The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is a widely used patient reported outcome in osteoarthritis. An important, but frequently overlooked, aspect of validating health outcome measures is to establish if items exhibit differential item functioning (DIF). That is, if respondents have the same underlying level of an attribute, does the item give the same score in different subgroups or is it biased towards one subgroup or another. The aim of the study was to explore DIF in the Likert format WOMAC for the first time in a UK osteoarthritis population with respect to demographic, social, clinical and psychological factors. Methods: The sample comprised a community sample of 763 people with osteoarthritis who participated in the Somerset and Avon Survey of Health. The WOMAC was explored for DIF by gender, age, social deprivation, social class, employment status, distress, body mass index and clinical factors. Ordinal regression models were used to identify DIF items. Results: After adjusting for age, two items were identified for the physical functioning subscale as having DIF with age identified as the DIF factor for 2 items, gender for 1 item and body mass index for 1 item. For the WOMAC pain subscale, for people with hip osteoarthritis one item was identified with age-related DIF. The impact of the DIF items rarely had a significant effect on the conclusions of group comparisons. Conclusions: Overall, the WOMAC performed well with only a small number of DIF items identified. However, as DIF items were identified in for the WOMAC physical functioning subscale it would be advisable to analyse data taking into account the possible impact of the DIF items when weight, gender or especially age effects, are the focus of interest in UK-based osteoarthritis studies. Similarly for the WOMAC pain subscale in people with hip osteoarthritis it would be worthwhile to analyse data taking into account the possible impact of the DIF item when age comparisons are of primary interest

A phase I trial of S-1 with concurrent radiotherapy for locally advanced pancreatic cancer

This study investigated the maximum tolerated dose of S-1 based on the frequency of its dose-limiting toxicities (DLT) with concurrent radiotherapy in patients with locally advanced pancreatic cancer. S-1 was administered orally at escalating doses from 50 to 80 mg m−2 b.i.d. on the day of irradiation during radiotherapy. Radiation therapy was delivered through four fields as a total dose of 50.4 Gy in 28 fractions over 5.5 weeks, and no prophylactic nodal irradiation was given. Twenty-one patients (50 three; 60 five; 70 six; 80 mg m−2 seven patients) were enrolled in this trial. At a dose of 70 mg m−2 S-1, two of six patients demonstrated DLT involving grade 3 nausea and vomiting and grade 3 haemorrhagic gastritis, whereas no patients at doses other than 70 mg m−2 demonstrated any sign of DLT. Among the 21 enrolled patients, four (19.0%) showed a partial response. The median progression-free survival time and median survival time for the patients overall were 8.9 and 11.0 months, respectively. The recommended dose of S-1 therapy with concurrent radiotherapy is 80 mg m−2 day−1. A multi-institutional phase II trial of this regimen in patients with locally advanced pancreatic cancer is now underway

Cross-Platform Microarray Data Normalisation for Regulatory Network Inference

Background Inferring Gene Regulatory Networks (GRNs) from time course microarray data suffers from the dimensionality problem created by the short length of available time series compared to the large number of genes in the network. To overcome this, data integration from diverse sources is mandatory. Microarray data from different sources and platforms are publicly available, but integration is not straightforward, due to platform and experimental differences. Methods We analyse here different normalisation approaches for microarray data integration, in the context of reverse engineering of GRN quantitative models. We introduce two preprocessing approaches based on existing normalisation techniques and provide a comprehensive comparison of normalised datasets. Conclusions Results identify a method based on a combination of Loess normalisation and iterative K-means as best for time series normalisation for this problem