Multi-Objective ROC learning for classification

Receiver operating characteristic (ROC) curves are widely used for evaluating classifier performance, having been applied to e.g. signal detection, medical diagnostics and safety critical systems. They allow examination of the trade-offs between true and false positive rates as misclassification costs are varied. Examination of the resulting graphs and calcu- lation of the area under the ROC curve (AUC) allows assessment of how well a classifier is able to separate two classes and allows selection of an operating point with full knowledge of the available trade-offs. In this thesis a multi-objective evolutionary algorithm (MOEA) is used to find clas- sifiers whose ROC graph locations are Pareto optimal. The Relevance Vector Machine (RVM) is a state-of-the-art classifier that produces sparse Bayesian models, but is unfor- tunately prone to overfitting. Using the MOEA, hyper-parameters for RVM classifiers are set, optimising them not only in terms of true and false positive rates but also a novel measure of RVM complexity, thus encouraging sparseness, and producing approximations to the Pareto front. Several methods for regularising the RVM during the MOEA train- ing process are examined and their performance evaluated on a number of benchmark datasets demonstrating they possess the capability to avoid overfitting whilst producing performance equivalent to that of the maximum likelihood trained RVM. A common task in bioinformatics is to identify genes associated with various genetic conditions by finding those genes useful for classifying a condition against a baseline. Typ- ically, datasets contain large numbers of gene expressions measured in relatively few sub- jects. As a result of the high dimensionality and sparsity of examples, it can be very easy to find classifiers with near perfect training accuracies but which have poor generalisation capability. Additionally, depending on the condition and treatment involved, evaluation over a range of costs will often be desirable. An MOEA is used to identify genes for clas- sification by simultaneously maximising the area under the ROC curve whilst minimising model complexity. This method is illustrated on a number of well-studied datasets and ap- plied to a recent bioinformatics database resulting from the current InChianti population study. Many classifiers produce “hard”, non-probabilistic classifications and are trained to find a single set of parameters, whose values are inevitably uncertain due to limited available training data. In a Bayesian framework it is possible to ameliorate the effects of this parameter uncertainty by averaging over classifiers weighted by their posterior probabil- ity. Unfortunately, the required posterior probability is not readily computed for hard classifiers. In this thesis an Approximate Bayesian Computation Markov Chain Monte Carlo algorithm is used to sample model parameters for a hard classifier using the AUC as a measure of performance. The ability to produce ROC curves close to the Bayes op- timal ROC curve is demonstrated on a synthetic dataset. Due to the large numbers of sampled parametrisations, averaging over them when rapid classification is needed may be impractical and thus methods for producing sparse weightings are investigated

Acid-catalysed carboxymethylation, methylation and dehydration of alcohols and phenols with dimethyl carbonate under mild conditions

Dimethyl carbonate (DMC) chemistry has been extended to include acid-catalysed reactions of different aliphatic alcohols and phenols. For the first time, p-toluenesulfonic acid (PTSA), H2SO4, AlCl3 and FeCl3 have been shown to aid carboxymethylation for primary aliphatic alcohols at catalytic loadings with quantitative conversion and selectivity. For carboxymethylation of secondary alcohols, stoichiometric PTSA and catalytic AlCl3 both gave quantitative conversion and selectivity. Stoichiometric FeCl3 and H2SO4 promoted dehydration of linear aliphatic alcohols. Additionally FeCl3 catalysed methylation of cyclohexanol, whilst AlCl3 resulted in methylation of phenolic compounds. This research expands the range of potential application for DMC in green chemistry

Challenges in the development of bio-based solvents : A case study on methyl(2,2-dimethyl-1,3-dioxolan-4-yl)methyl carbonate as an alternative aprotic solvent

Many traditional solvents have drawbacks including sustainability and toxicity issues. Legislations such as REACH is driving the move towards less hazardous chemicals and production processes. Therefore, safer bio-based solvents need to be developed. Herein, a 10 step method has been proposed for the development of new bio-based solvents that utilise a combination of in silico modelling of Hansen solubility parameters (HSPs), experimental Kamlet-Abboud-Taft parameters, selection of green synthetic routes followed by applications testing and toxicity measurements. The challenges that the chemical industry face in the development of new bio-based solvents are highlighted through a case study on methyl (2,2-dimethyl-1,3-dioxolan-4-yl) methyl carbonate (MMC) which can be synthesised from glycerol. Although MMC is an attractive candidate as a replacement solvent, simply being bio-derived is not enough for a molecule to be regarded as green. The methodology of solvent development described here is a broadly applicable protocol that will indicate if a new bio-based solvent is functionally proficient, but will also highlight the importance of early stage Kamlet-Abboud-Taft parameters determination and toxicity testing in the development of a green solvent

Mercury Orbiter: Report of the Science Working Team

The results are presented of the Mercury Orbiter Science Working Team which held three workshops in 1988 to 1989 under the auspices of the Space Physics and Planetary Exploration Divisions of NASA Headquarters. Spacecraft engineering and mission design studies at the Jet Propulsion Lab were conducted in parallel with this effort and are detailed elsewhere. The findings of the engineering study, summarized herein, indicate that spin stabilized spacecraft carrying comprehensive particles and fields experiments and key planetology instruments in high elliptical orbits can survive and function in Mercury orbit without costly sun shields and active cooling systems

Application of bio-based solvents for biocatalysed synthesis of amides with Pseudomonas stutzeri lipase (PSL)

Bio-based solvents were investigated for the biocatalysed amidation reactions of various ester-amine combinations by Pseudomonas stutzeri lipase (PSL). Reactions were undertaken in a range of green and potentially bio-based solvents including terpinolene, p-cymene, limonene, 2-methyl THF, ɣ-valerolactone, propylene carbonate, dimethyl isosorbide, glycerol triacetate and water. Solvent screenings demonstrated the importance and potential of using non-polar bio-based solvents for favouring aminolysis over hydrolysis; whilst substrate screenings highlighted the unfavourable impact of reactants bearing bulky para- or 4-substituents. Renewable terpene-based solvents (terpinolene, p-cymene, D-limonene) were demonstrated to be suitable bio-based media for PSL amidation reactions. Such solvents could provide a greener and more sustainable alternative to traditional petrochemical derived non-polar solvents. Importantly, once the enzyme (either PSL or CALB) binds with a bulky para-substituted substrate, only small reagents are able to access the active site. This therefore limits the possibility for aminolysis to take place, thereby promoting the hydrolysis. This mechanism of binding supports the widely accepted 'Ping Pong - Bi Bi' mechanism used to describe enzyme kinetics. The work highlights the need to further investigate enzyme activity in relation to para- or 4-substituted substrates. A priority in PSL chemistry remains a methodology to tackle the competing hydrolysis reaction

DFT and experimental analysis of aluminium chloride as a Lewis acid proton carrier catalyst for dimethyl carbonate carboxymethylation of alcohols

The Lewis acid catalysed mechanism of dimethyl carbonate (DMC) mediated carboxymethylation of alcohol was investigated experimentally and through computational chemistry methods including density functional theory (DFT). Experimental data showed that catalytic loading of AlCl3 enabled the quantitative carboxymethylation of octanol in less than 20 h, while in the absence of a catalyst only trace product was observed. The geometry of the identified transition states and related energy barriers indicate that the activation energies in AlCl3 catalysed pathways are significantly lower than those in catalyst-free pathways. Theoretical quantum chemistry methods were utilised to explore and analyse the complex of DMC with AlCl3. Natural bond orbital theory analysis and molecular orbital analysis demonstrated that the dipole present in Al-Cl covalent bonding plays a vital role in assisting the proton-transfer process. Most importantly, the reaction mechanism disclosed in this research can aid in the exploration of new Lewis acid catalysed processes in the field of dialkyl carbonate chemistry

Valorization of spruce needle waste via supercritical extraction of waxes and facile isolation of nonacosan-10-ol

Supercritical carbon dioxide was utilized as a sustainable alternative to solvent extraction of waxes from the waste needles of two spruce species, namely Norwegian and Sitka spruce. These extracts were rich in nonacosan-10-ol, an organic compound with hydrophobic properties that lends its use in the preparation of superhydrophobic coatings. The highest crude yields were 1.7% w/w of needles obtained at 400 bar and 60 °C, while nonacosan-10-ol was selectively extracted at 200 bar and 60 °C (8070 ± 91.1 μg/g of needles). Purification of nonacosan-10-ol from the wax extracts was conducted using a simple rapid green recrystallization technique. This yielded a recovery of 44.6% ± 2% and 48.4% ± 2% of the total nonacosan-10-ol from the original crude Sitka (3600 μg/g of needles) and Norwegian wax (1920 μg/g of needles) respectively. Application of nonacosan-10-ol to a filter paper led to the formation of highly hydrophobic surfaces, with preliminary contact angles of up to 149°. This sustainable production method may develop opportunities to valorize forestry waste within a holistic biorefinery

Causes of death among homeless people: a population-based cross-sectional study of linked hospitalisation and mortality data in England. [version 1; peer review: 2 approved]

Background: Homelessness has increased by 165% since 2010 in England, with evidence from many settings that those affected experience high levels of mortality. In this paper we examine the contribution of different causes of death to overall mortality in homeless people recently admitted to hospitals in England with specialist integrated homeless health and care (SIHHC) schemes.  Methods: We undertook an analysis of linked hospital admission records and mortality data for people attending any one of 17 SIHHC schemes between 1st November 2013 and 30th November 2016. Our primary outcome was death, which we analysed in subgroups of 10th version international classification of disease (ICD-10) specific deaths; and deaths from amenable causes. We compared our results to a sample of people living in areas of high social deprivation (IMD5 group). Results: We collected data on 3,882 individual homeless hospital admissions that were linked to 600 deaths. The median age of death was 51.6 years (interquartile range 42.7-60.2) for SIHHC and 71.5 for the IMD5 (60.67-79.0).  The top three underlying causes of death by ICD-10 chapter in the SIHHC group were external causes of death (21.7%; 130/600), cancer (19.0%; 114/600) and digestive disease (19.0%; 114/600).  The percentage of deaths due to an amenable cause after age and sex weighting was 30.2% in the homeless SIHHC group (181/600) compared to 23.0% in the IMD5 group (578/2,512). Conclusion: Nearly one in three homeless deaths were due to causes amenable to timely and effective health care. The high burden of amenable deaths highlights the extreme health harms of homelessness and the need for greater emphasis on prevention of homelessness and early healthcare interventions

Outcomes of specialist discharge coordination and intermediate care schemes for patients who are homeless: analysis protocol for a population-based historical cohort

Introduction People who are homeless often experience poor hospital discharge arrangements, reflecting ongoing care and housing needs. Specialist integrated homeless health and care provision (SIHHC) schemes have been developed and implemented to facilitate the safe and timely discharge of homeless patients from hospital. Our study aims to investigate the health outcomes of patients who were homeless and seen by a selection of SIHHC services. Methods and analysis Our study will employ a historical population-based cohort in England. We will examine health outcomes among three groups of adults: (1) homeless patients seen by specialist discharge schemes during their hospital admission; (2) homeless patients not seen by a specialist scheme and (3)admitted patients who live in deprived neighbourhoods and were not recorded as being homeless. Primary outcomes will be: time from discharge to next hospital inpatient admission; time from discharge to next accident and emergency attendance and 28-day emergency readmission. Outcome data will be generated through linkage to hospital admissions data (Hospital Episode Statistics) and mortality data for November 2013 to November 2016. Multivariable regression will be used to model the relationship between the study comparison groups and each of the outcomes. Ethics and dissemination Approval has been obtained from the National Health Service (NHS) Confidentiality Advisory Group (reference 16/CAG/0021) to undertake this work using unconsented identifiable data. Health Research Authority Research Ethics approval (REC 16/EE/0018) has been obtained in addition to local research and development approvals for data collection at NHS sites. We will feedback the results of our study to our advisory group of people who have lived experience of homelessness and seek their suggestions on ways to improve or take this work further for their benefit. We will disseminate our findings to SIHHC schemes through a series of regional workshops

Using in vivo nickel to direct the pyrolysis of hyperaccumulator plant biomass : In vivo nickel to direct the pyrolysis of hyperaccumulator plant biomass

The effects of naturally occurring nickel in hyperaccumulator plants used for phytoremediation of contaminated soils on the microwave (MW) biomass pyrolysis are described for the first time. The presence of natural nickel appears to protect the hemicellulose component of the plant leading to 3 times lower yields of bio-gas and increased quantities of bio-char. The composition of the bio-oil is also affected