Electrostatic charging of non-polar colloids by reverse micelles

Colloids dispersed in a non-polar solvent become charged when reverse micelles are added. We study the charge of individual sterically-stabilized poly(methyl methacrylate) spheres dispersed in micellar solutions of the surfactants sodium bis(2-ethyl 1-hexyl) sulfosuccinate [AOT], zirconyl 2-ethyl hexanoate [Zr(Oct)$_{2}$], and a copolymer of poly(12-hydroxystearic acid)--poly(methyl methacrylate) [PHSA-PMMA]. Although the sign of the particle charge is positive for Zr(Oct)$_{2}$, negative for AOT, and essentially neutral for PHSA-PMMA the different micellar systems display a number of common features. In particular, we demonstrate that, over a wide range of concentrations, the colloid charge is independent of the number of micelles added and scales linearly with the colloid size. A simple thermodynamic model, in which the particle charge is generated by the competitive adsorption of both positive and negative micelles, is in good agreement with the experimental data

Performance Factors and Management Practices Related to Earnings of East Central North Dakota Crop Farms

Agricultural Finance, Farm Management,

Visual analysis of social networks in space and time using smartphone logs

We designed and applied novel interactive visualisation to investigate how social networks - derived from smartphone logs - are embedded in time and space. Social networks were identified through direct calls between participants and calls to mutual contacts of participants. Direct contact between participants was sparse and deriving networks through mutual contacts helped enrich the social networks. Our resulting interactive visualisation tool offers four linked and co-ordinated views of spatial, temporal, individual and social network aspects of the data. Brushing and altering techniques help us investigate how these aspects relate. We also simultaneously display some demographic and attitudinal variables to help add context to the behaviours we observe. Using these techniques, we were able to characterise spatial and temporal aspects of participants' social networks and suggest explanations for some of them. We reflect on the extent to which such analysis helps us understand social communication behaviour

Timebias corrections to predictions

The importance of an accurate knowledge of the time bias corrections to predicted orbits to a satellite laser ranging (SLR) observer, especially for low satellites, is highlighted. Sources of time bias values and the optimum strategy for extrapolation are discussed from the viewpoint of the observer wishing to maximize the chances of getting returns from the next pass. What is said may be seen as a commercial encouraging wider and speedier use of existing data centers for mutually beneficial exchange of time bias data

The evolution of infantry brigade command in the British Army on the Western Front, 1916-1918

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.This thesis challenges the orthodox view that the role of the infantry brigade command of the British Army during the First World War was unduly narrow. Instead, it is argued that the response of the brigadiers and their staff to the challenges of the Western Front secured their role as agents of organisational and tactical change. A series of case studies over the period 1916-1918 serve to demonstrate the significant contribution of brigade staff to the Army’s learning process. Much like that of the wider BEF however, this process was complex and uneven. As a consequence, the development and battlefield performance of the brigades varied in accordance with factors of an external and internal nature: of these, the influence of the corps or division under which a brigade served was fundamental

The impact of students’ perceived relatedness and competence upon their motivated engagement with learning activities: a self-determination theory perspective

Empirical research that has applied Self-Determination Theory (SDT) within classrooms suggests that the combined satisfaction of three basic psychological needs can be predictive of students’ motivation to engage with learning activities. These three basic needs are relatedness, which, for the purposes of the current research, takes the form of a positive teacher-student relationship, perceived self-competence, and autonomy. The current research suggests that, whilst SDT emphasizes the importance of autonomy as a basis for self-determined engagement with learning, the motivation to be autonomous is a potential outcome informed by the students’ perceived competence and the perceived quality of the teacher-student relationship. These findings were the basis for three posits regarding the impact of the satisfaction of the three basic psychological needs, central to SDT, upon students’ engagement with learning activities. These posits are: that firstly, an individual’s motivation to be autonomous (SDT; autonomy) is an outcome dependent upon students’ satisfied needs for both a positive teacher-student relationship (SDT: relatedness) and perceived competence (SDT: competence); secondly, that perceived competence is informed by and reciprocally informs the quality of the teacher-student relationship; and thirdly, that there is a potential cumulative connection between students’ perceived competence and the quality of the teacher-student relationship, in terms of the combined impact upon the quality and persistence of autonomous motivation. These interpretive claims emerged from and were supported by the findings across the main study and triangulation methods within the current research. The current research begins to unravel how the motivational interplay between the three SDT-centred basic psychological needs may inform students’ engagement with learning activities in formal learning settings. This led to the development of a proposed SDT-embedded motivational pathways model. This model is worthy of further testing, explanation and modification by educators through classroom-based research

Studying commuting behaviours using collaborative visual analytics

Mining a large origin–destination dataset of journeys made through London’s Cycle Hire Scheme (LCHS), we develop a technique for automatically classifying commuting behaviour that involves a spatial analysis of cyclists’ journeys. We identify a subset of potential commuting cyclists, and for each individual define a plausible geographic area representing their workplace. All peak-time journeys terminating within the vicinity of this derived workplace in the morning, and originating from this derived workplace in the evening, we label commutes. Three techniques for creating these workplace areas are compared using visual analytics: a weighted mean-centres calculation, spatial k-means clustering and a kernel density-estimation method. Evaluating these techniques at the individual cyclist level, we find that commuters’ peak-time journeys are more spatially diverse than might be expected, and that for a significant portion of commuters there appears to be more than one plausible spatial workplace area. Evaluating the three techniques visually, we select the density-estimation as our preferred method. Two distinct types of commuting activity are identified: those taken by LCHS customers living outside of London, who make highly regular commuting journeys at London’s major rail hubs; and more varied commuting behaviours by those living very close to a bike-share docking station. We find evidence of many interpeak journeys around London’s universities apparently being taken as part of cyclists’ working day. Imbalances in the number of morning commutes to, and evening commutes from, derived workplaces are also found, which might relate to local availability of bikes. Significant decisions around our workplace analysis, and particularly these broader insights into commuting behaviours, are discovered through exploring this analysis visually. The visual analysis approach described in the paper is effective in enabling a research team with varying levels of analysis experience to participate in this research. We suggest that such an approach is of relevance to many applied research contexts