Arsenic-glutathione complexes - Their stability in solution and during separation by different HPLC modes

Complexes of arsenic compounds and glutathione are believed to play an essential part in the metabolism and transport of inorganic arsenic and its methylated species. Up to now, the evidence of their presence is mostly indirect. We studied the stability and Chromatographic behaviour of glutathione complexes with trivalent arsenic: i.e. As^III(GS)₃, MA ^III(GS)₂ and DMA^III(GS) under different conditions. Standard ion chromatography using PRP X-100 and carbonate or formic acid buffer disintegrated the complexes, while all three complexes are stable and separable by reversed phase chromatography (0.1% formic acid/acetonitrile gradient). As^III(GS)₃ and MA^III(GS)₂ were more stable than DMA^III(GS), which even under optimal conditions tended to degrade on the column at 25 °C. Chromatography at 6 °C can retain the integrity of the samples. These results shed more light on the interpretation of a vast number of previously published arsenic speciation studies, which have used Chromatographic separation techniques with the assumption that the integrity of the arsenic species is guaranteed. © The Royal Society of Chemistry 2004.

Identification of arsenic species in sheep-wool extracts by different chromatographic methods

Sheep on the island of North Ronaldsay (Orkney, UK) feed mostly on seaweed, which contains high concentrations of dimethylated arsenoribosides. Wool of these sheep contains dimethylated, monomethylated and inorganic arsenic, in addition to unidentified arsenic species in unbound and complexed form. Chromatographic techniques using different separation mechanisms and detectors enabled us to identify five arsenic species in water extracts of wool. The wool contained 5.2 ± 2.3 μg arsenic per gram wool. About 80% of the arsenic in wool was extracted by boiling the wool with water. The main species is dimethylarsenic, which accounted for about 75 to 85%, monomethylated arsenic at about 5% and the rest is inorganic arsenic. Depending on the separation method and condition, the chromatographic recovery of arsenic species was between 45% for the anion exchange column, 68% for the size exclusion chromatography (SEC) and 82% for the cation exchange column. The SEC revealed the occurrence of two unknown arsenic compounds, of which one was probably a high molecular mass species. Since chromatographic recovery can be improved by either treating the extract with CuCl/HCl (CAT: 90%) or longer storage of the sample (CAT: 105%), in particular for methylated arsenic species, it can be assumed that labile arsenic -protein-like coordination species occur in the extract, which cannot be speciated with conventional chromatographic methods. It is clear from our study of sheep wool that there can be different kinds of 'hidden' arsenic in biological matrices, depending on the extraction, separation and detection methods used. Hidden species can be defined as species that are not recordable by the detection system, not extractable or do not elute from chromatographic columns. Copyright © 2003 John Wiley & Sons, Ltd.

Performance of sustainable SCC mixes with mineral additions for use in precast concrete industry

The aim of this research was to study the impact that different mineral powders have on the properties of self-compacting concrete (SCC) in order to obtain relations that make it possible to optimize their dosages for being used in precast concrete applications. Different combinations and contents of cement, mineral additions (active and inert), superplasticizers, and aggregates are considered. A new approach for determining the saturation point of superplasticizers is introduced. The fresh state performance was assessed by means of the following tests: slump flow, V-funnel, and J-ring. Concrete compressive strength values at different ages up to 56 days have been retained as representative of the materials’ performance in its hardened state. All these properties have been correlated with SCC proportioning. As a result, a number of recommendations for the precast concrete industry arise to design more stable SCC mixes with a reduced carbon footprint.

Spectacles of military urbanism in online representations of the Elite Squad of the military police of Rio de Janeiro: a multimodal approach

This paper presents a multimodal analysis of online self-representations of the Elite Squad of the military police of Rio de Janeiro, the Special Police Operations Battalion BOPE. The analysis is placed within the wider context of a “new military urbanism”, which is evidenced in the ongoing “Pacification” of many of the city’s favelas, in which BOPE plays an active interventionist as well as a symbolic role, and is a kind of solution which clearly fails to address the root causes of violence which lie in poverty and social inequality. The paper first provides a sociocultural account of BOPE’s role in Rio’s public security and then looks at some of the mainly visual mediated discourses the Squad employs in constructing a public image of itself as a modern and efficient, yet at the same time “magical” police force.

Multimodal Critical Discourse Analysis (MCDA)

Critical Discourse Analysis (CDA) has probably made the most comprehensive attempt to develop a theory of the inter-connectedness of discourse, power and ideology and is specifically concerned with the role that discourse plays in main-taining and legitimizing inequality in society. While CDA’s general thrust has been towards the analysis of linguistic structures, some critical discourse analysts have begun to focus on multimodal discourses because of the increasingly impor-tant role these play in many social and political contexts. Still, a great deal of CDA analysis has remained largely monomodal. The principal aim of this chapter is therefore to address this situation and demonstrate in what ways CDA can be deployed to analyse the ways that ideological discourses can be communicated, naturalised and legitimated beyond the linguistic level. The chapter also offers a rationale for a multimodal approach based on Halliday’s Systemic Functional Linguistics (SFL), by which it is directly informed

Institutional Discourse

Institutions (and how they work) have long been the object of many investigations in the fields of media, cultural, and organizational studies. More recently, there has been a “linguistic” turn in the study of institutions with many language-focused explo- rations of how power and discourse may function in specific institutional and organi- zational settings, such as schools, courtrooms, corporations, clinics, hospitals, and pris- ons. Many of these studies have been concerned with the ways in which language is used to create and shape institutions and how institutions in turn have the capacity to create, shape, and impose discourses on people. Institutions thus have considerable control over the organizing of our routine experiences of the world and the way we classify that world. They also have the power to foster particular kinds of identities to suit their own purposes.

The impact of organisational factors and government policy on psychiatric nurses family focused practice with parents who have mental illness, their dependent children and families in Ireland

Government policy and organizational factors influence family focused practice in adult mental health services. However, how these aspects shape psychiatric nurses’ practice with parents who have mental illness, their dependent children and families is less well understood. Drawing on the findings of a qualitative study, this article explores the way in which Irish policy and organizational factors might influence psychiatric nurses’ family focused practice, and whether (and how) family focused practice might be further promoted. A purposive sample of 14 psychiatric nurses from eight mental health services completed semi-structured interviews in 2013. The analysis was inductive and presented as thematic networks. Both groups described how policies and organizational culture enabled and/or hindered family focused practice, with differences between community and acute participants seen. The need to develop national and international policies along with practices to embed information and support regarding parenting into ongoing care is implicated in this study.

Picturing Probation: Exploring the utility of visual methods in comparative research

A previous review of research on the practice of offender supervision identified the predominant use of interview-based methodologies and limited use of other research approaches (Robinson and Svensson, 2013). It also found that most research has tended to be locally focussed (i.e. limited to one jurisdiction) with very few comparative studies. This article reports on the application of a visual method in a small-scale comparative study. Practitioners in five European countries participated and took photographs of the places and spaces where offender supervision occurs. The aims of the study were two-fold: firstly to explore the utility of a visual approach in a comparative context; and secondly to provide an initial visual account of the environment in which offender supervision takes place. In this article we address the first of these aims. We describe the application of the method in some depth before addressing its strengths and weaknesses. We conclude that visual methods provide a useful tool for capturing data about the environments in which offender supervision takes place and potentially provide a basis for more normative explorations about the practices of offender supervision in comparative contexts.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.