Methane Activation and Functionalisation using Zinc-Modified Zeolites

This thesis has investigated methane activation and subsequent functionalisation over zinc-modified zeolites, predominantly where the zinc has been introduced by vapour deposition. Particular focus was paid to the role of the zeolite framework and the nature of the zinc active site on methane activation. Selective methane activation to form [ZnII-CH3] species was confirmed by 13C MAS NMR spectroscopy for three zeolite frameworks with substantially different micropore topologies (ZSM-5 (15), FER (10) and MOR (10)). For Zn(VD)/MOR, two signals were observed by 13C NMR spectroscopy, likely resulting from two distinct [ZnII-CH3] species present in the 12 MR and 8 MR side pockets, as supported by additional NMR experiments. The percentage of active zinc sites, measured through quantitative NMR spectroscopic studies, varied with the zeolite framework and was found to be ZSM‐5 (5.7 %), MOR (1.2 %) and FER (0.5 %). Furthermore, the vapour deposition sample Zn(VD)/CH4/ZSM-5 produced significantly higher levels of active zinc sites compared to the Zn(IE)/CH4/ZSM-5 ion exchanged sample (5.7% compared with 0.9%) highlighting that both zeolite framework and method of zinc introduction influence methane activation. The observed products of oxidation of the [ZnII-CH3] species are also shown to depend on the zeolite framework type and the oxidative conditions used. XANES analysis of the vapour deposition (VD) samples, Zn(VD)/ZSM-5 and Zn(VD)/MOR, highlighted the presence of a low energy band tentatively assigned to a [ZnI-ZnI] dimeric species. Samples prepared by ion exchange or zinc vapour deposition samples heated to 600 °C, which are no longer able to activate methane, do not show this lower energy band. EXAFS analysis suggested the VD samples can be fitted using a model containing both Zn-O and [ZnI-ZnI] in the first co-ordination sphere whilst IE and 600 °C sample can only be fitted using Zn-O. The XAS evidence supported by futher experiments led us to conclude that the [ZnI-ZnI] dimer is the active species in vapour deposition samples. Zinc catalysts prepared through zinc vapour deposition, ion exchange and impregnation using four different zeolite frameworks (ZSM-5 (12.5), BETA (12.5), MOR (10) and FER(10)) were tested for activity in the methane dehydroaromatisation (MDA) reaction. Overall, zeolite framework plays a key role in the MDA reaction with ZSM-5 proving to be the best host framework, in line with results presented in the literature for Mo catalysts. The method of zinc introduction, and therefore the active zinc species, was also crucial as zinc introduction by vapour deposition proved superior to both ion exchange and impregnation

Reconstruction of a midfacial defect using an intraoral-extraoral combination prosthesis employing magnets: a clinical report

Radical maxillectomy frequently leads to extended defects in hard and soft tissues that result in a connection between the oral cavities and orbit. If the defect cannot be surgically reconstructed, a combination prosthesis may be necessary to remedy dysfunction in patient function, comfort, esthetics. For minor defects, enlargement of the base of the intra oral prosthesis is generally sufficient. Resections that affect more than one third of the maxilla usually require an intra oral and an extra oral prosthesis that could be assembled and retained in the patient. This clinical report describes a technique of prosthetic rehabilitation of midfacial defect with a silicone orbital prosthesis and intra oral obturator that are retained by magnets

Short-term exposure to carbon monoxide and myocardial infarction: A systematic review and meta-analysis

BACKGROUND: Previous studies suggest an association between short-term exposure to carbon monoxide and myocardial infarction. We performed a systematic review and meta-analysis to assess current evidence on this association to support the update of the World Health Organization (WHO) Global Air Quality Guidelines. METHODS: We searched Medline, Embase and Cochrane Central Register of Controlled Trials to update the evidence published in a previous systematic review up to 30th September 2018 for studies investigating the association between short-term exposure to ambient carbon monoxide (up to lag of seven days) and emergency department visits or hospital admissions and mortality due to myocardial infarction. Two reviewers assessed potentially eligible studies and performed data extraction independently. Random-effects meta-analysis was used to derive the pooled risk estimate per 1 mg/m3 increase in ambient carbon monoxide concentration. Risk of bias in individual studies was assessed using a domain-based assessment tool. The overall certainty of the body of evidence was evaluated using an adapted certainty of evidence assessment framework. RESULTS: We evaluated 1,038 articles from the previous review and our updated literature search, of which, 26 satisfied our inclusion criteria. Overall, myocardial infarction was associated with exposure to ambient carbon monoxide concentration (risk ratio of 1.052, 95% confidence interval 1.017-1.089 per 1 mg/m3 increase). A third of studies were assessed to be at high risk of bias (RoB) due to inadequate adjustment for confounding. Using an adaptation of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework, the overall evidence was assessed to be of moderate certainty. CONCLUSIONS: This review demonstrated that the pooled risk ratio for myocardial infarction was 1.052 (95% CI 1.017-1.089) per 1 mg/m3 increase in ambient carbon monoxide concentration. However, very few studies originated from low- and middle-income countries

Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study.

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001-2010) with complete data on all covariates. Variables were artificially made "missing at random," and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data