The majority-minority conundrum in Northern Ireland::An Orange Order perspective

Researchers have argued that, depending on the framing of the Northern Ireland conflict, each group could either be a minority or a majority relative to the other. This complicates macrosocial explanations of the conflict which make specific predictions on the basis of minority or majority positions. The present paper argues that this conundrum may have arisen from the inherent variability in microidentity processes that do not fit easily with macroexplanations. In this paper the rhetoric of relative group position is analysed in political speeches delivered by leading members of an influential Protestant institution in Northern Ireland. It is apparent that minority and majority claims are not fixed but are
flexibly used to achieve local rhetorical goals. Furthermore, the speeches differ before and after the Good Friday Agreement, with a reactionary “hegemonic” Unionist position giving way to a “majority-rights power sharing” argument and a “pseudo-minority” status giving way to a “disempowered minority” argument. These results suggest a view of the Northern Ireland conflict as a struggle for “symbolic power,” i.e., the ability to flexibly define the intergroup situation to the ingroup’s advantage.

Risk minimization in logistic processes with oil products

13.Vidovic M., Miljus M., Vlajic J., (2002), "Risk minimization in logistic processes with oil products", Proceedings of the 6th International Conference on Traffic Science, ICTS 2002, Portorož, Slovenia, pp. 568-577;

Development of a novel continuous statistical modelling technique for detecting the adulteration of extra virgin olive oil with hazelnut oil by using spectroscopic data

The adulteration of extra virgin olive oil with other vegetable oils is a certain problem with economic and health consequences. Current official methods have been proved insufficient to detect such adulterations. One of the most concerning and undetectable adulterations with other vegetable oils is the addition of hazelnut oil. The main objective of this work was to develop a novel dimensionality reduction technique able to model oil mixtures as a part of an integrated pattern recognition solution. This final solution attempts to identify hazelnut oil adulterants in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. The proposed Continuous Locality Preserving Projections (CLPP) technique allows the modelling of the continuous nature of the produced in house admixtures as data series instead of discrete points. This methodology has potential to be extended to other mixtures and adulterations of food products. The maintenance of the continuous structure of the data manifold lets the better visualization of this examined classification problem and facilitates a more accurate utilisation of the manifold for detecting the adulterants.

Identification of vegetable oil botanical speciation in refined vegetable oil blends using an innovative combination of chromatographic and spectroscopic techniques

European Regulation 1169/2011 requires producers of foods that contain refined vegetable oils to label the oil types. A novel rapid and staged methodology has been developed for the first time to identify common oil species in oil blends. The qualitative method consists of a combination of a Fourier Transform Infrared (FTIR) spectroscopy to profile the oils and fatty acid chromatographic analysis to confirm the composition of the oils when required. Calibration models and specific classification criteria were developed and all data were fused into a simple decision-making system. The single lab validation of the method demonstrated the very good performance (96% correct classification, 100% specificity, 4% false positive rate). Only a small fraction of the samples needed to be confirmed with the majority of oils identified rapidly using only the spectroscopic procedure. The results demonstrate the huge potential of the methodology for a wide range of oil authenticity work.

Quantum yield measurements for the photocatalytic oxidation of Acid Orange 7 (AO7) and reduction of 2,6-dichloroindophenol (DCIP) on transparent TiO2 films of various thickness

This work comprises the photoactivity assessment of transparent sol–gel TiO2 coatings of various thickness using two test systems. The initial rates of both photocatalytic reactions, namely the oxidative bleaching of Acid Orange 7 (AO7) and the reductive bleaching of 2,6-dichlorindophenol (DCIP) increase linearly with increasing titania film thickness as well as with increasing absorbed light flux. The latter work revealed quantum yields (QY) of 0.19% and 92% for the AO7 and DCIP test system, respectively. The low QY for the AO7 oxidation is due to the combination of a slow irreversible reduction of oxygen and also for the oxidation of AO7, thus favouring the high efficiency for electron–hole recombination that is typical for aqueous organic pollutants. In contrast, the very high QY for the photocatalysed reduction of DCIP is due to the presence of a vast excess of glycerol which traps the photogenerated holes efficiently and so allow time for the slower reduction of dye to take place. Furthermore, the oxidation of glycerol results in the generation of highly reducing R-hydroxyalkyl radicals that are able to also reduce DCIP. As a consequence of this ‘current doubling’ effect, the observed QY (92%) is much higher than the apparent theoretical value of 50%.

A new analytical approach for the detection of palm oil in vegetable oil blends

The new Food Information Regulation (1169/2011), dictates that in a refined vegetable oil blend, the type of oil must be clearly identified in the package in contract with current practice where is labelled under the generic and often misleading term “vegetable oil”. With increase consumer awareness in food authenticity, as shown in the recent food scandal with horsemeat in beef products, the identification of the origin of species in food products becomes increasingly relevant. Palm oil is used extensively in food manufacturing and as global demand increases, producing countries suffer from the aftermath of intensive agriculture. Even if only a small portion of global production, sustainable palm oil comes in great demand from consumers and industry. It is therefore of interest to detect the presence of palm oil in food products as consumers have the right to know if it is present in the product or not, mainly from an ethical point of view. Apart from palm oil and its derivatives, rapeseed oil and sunflower oil are also included. With DNA-based methods, the gold standard for the detection of food authenticity and species recognition deemed not suitable in this analytical problem, the focus is inevitably drawn to the chromatographic and spectroscopic methods. Both chromatographic (such as GC-FID and LC-MS) and spectroscopic methods (FT-IR, Raman, NIR) are relevant. Previous attempts have not shown promising results due to oils’ natural variation in composition and complex chemical signals but the suggested two-step analytical procedure is a promising approach with very good initial results.

Identifying oil species in oil mixtures

Detection of adulteration of non-processed vegetable oil with lesser value seed oils (classic example is hazelnut in virgin olive oil) has been in the centre of scientific attention for many years and several chemical methods were proposed. The recent EC Regulation 1169/2011, however, introduces necessity for different analytical method in a more complicated matrix. From the end of 2014, food businesses required to declare the composition of the refined oil mixture in the food product label. This creates a gap since there is no analytical method currently available to perform such analysis. In the first phase the work focused on 100% oil blends of various oil species of palm oil (and derivatives), sunflower and rapeseed oil before expanding to foodstuffs. Chromatographic methods remain highly relevant although suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques based on machine learning algorithms, however, when applied in FTIR, Raman spectroscopic data have a strong potential in tackling the problem.

Virgin Olive Oil: Losses of Antioxidant Polar Phenolic Compounds due to Storage, Packaging, and Culinary Uses

Virgin olive oil is a high quality natural product obtained only by physical means. In addition to triacylglycerols it contains nutritionally important polar and non-polar antioxidant phenols and other bioactive ingredients. The polar fraction is a complex mixture of phenolic acids, simple phenols, derivatives of the glycosides oleuropein and ligstroside, lignans, and flavonoids. These compounds contribute significantly to the stability, flavor, and biological value of virgin olive. In the various stages of production, during storage and in the culinary uses, polar phenols and other valuable bioactive ingredients may be damaged. Oxidation, photo-oxidation, enzymic hydrolysis and heating at frying temperatures have a serious adverse effect. Due to the biological importance of the oil and its unique character, analytical methods have been developed to evaluate antioxidant activity or analyse complex phenol mixtures. These are based on radical scavenging assays and chromatographic techniques. Hyphenated methods are also used including liquid chromatography-mass spectrometry and liquid chromatography-nuclear magnetic resonance spectroscopy.

The effect of pH on the photonic efficiency of the destruction of methyl orange under controlled periodic illumination with UV-LED sources

The nature of photon interaction and reaction pH can have significant impacts on semiconductor photocatalysis. This paper describes the effect of pH on the photonic efficiency of photocatalytic reactions in the aqueous phase using TiO2 catalysts. The reactor was irradiated using periodic illumination with UV-LEDs through control of the illumination duty cycle (γ) through a series of light and dark times (Ton/Toff). Photonic efficiencies for methyl orange degradation were found to be comparable at high γ irrespective of pH. At lower γ, pH effects on photonic efficiency were very distinct across acidic, neutral and alkaline pH indicating an effect of complementary parameters. The results suggest photonic efficiency is greatest as illumination time, Ton approaches interfacial electron-transfer characteristic time which is within the range of this study or charge-carrier lifetimes upon extrapolation and also when electrostatic attraction between surface-trapped holes, {TiIVOH}ads+ and substrate molecules is strongest.

Effect of controlled periodic-based illumination on the photonic efficiency of photocatalytic degradation of methyl orange

The use of controlled periodic illumination with UV LEDs for enhancing photonic efficiency of photocatalytic decomposition processes in water has been investigated using methyl orange as a model compound. The impact of the length of light and dark time periods (T _ON/T _OFF times) on photodegradation and photonic efficiency using a UV LED-illuminated photoreactor has been studied. The results have shown an inverse dependency of the photonic efficiency on duty cycle and a very little effect on T _ON or T _OFF time periods, indicating no effect of rate-limiting steps through mass diffusion or adsorption/desorption in the reaction. For this reactor, the photonic efficiency under controlled periodic illumination (CPI) matches to that of continuous illumination, for the same average UV light intensities. Furthermore, under CPI conditions, the photonic efficiency is inversely related to the average UV light intensity in the reactor, in the millisecond time regime. This is the first study that has investigated the effect of controlled periodic illumination using ultra band gap UV LED light sources in the photocatalytic destruction of dye compounds using titanium dioxide. The results not only enhance the understanding of the effect of periodic illumination on photocatalytic processes but also provide a greater insight to the potential of these light sources in photocatalytic reactions. 

Mathematical modelling of quantum yield enhancements of methyl orange photooxidation in aqueous TiO2 suspensions under controlled periodic UV LED illumination

Quantum yields of the photocatalytic degradation of methyl orange under controlled periodic illumination (CPI) have been modelled using existing models. A modified Langmuir-Hinshelwood (L-H) rate equation was used to predict the degradation reaction rates of methyl orange at various duty cycles and a simple photocatalytic model was applied in modelling quantum yield enhancement of the photocatalytic process due to the CPI effect. A good agreement between the modelled and experimental data was observed for quantum yield modelling. The modified L-H model, however, did not accurately predict the photocatalytic decomposition of the dye under periodic illumination.

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

The predominant fear in capital markets is that of a price spike. Commodity markets differ in that there is a fear of both upward and down jumps, this results in implied volatility curves displaying distinct shapes when compared to equity markets. The use of a novel functional data analysis (FDA) approach, provides a framework to produce and interpret functional objects that characterise the underlying dynamics of oil future options. We use the FDA framework to examine implied volatility, jump risk, and pricing dynamics within crude oil markets. Examining a WTI crude oil sample for the 2007–2013 period, which includes the global financial crisis and the Arab Spring, strong evidence is found of converse jump dynamics during periods of demand and supply side weakness. This is used as a basis for an FDA-derived Merton (1976) jump diffusion optimised delta hedging strategy, which exhibits superior portfolio management results over traditional methods.