Neuro-linguistic programming techniques to improve the self-efficacy of undergraduate dissertation students

This paper aims to address the gap in the extant literature examining the support offered to, and required by, students in light of the changing nature of the undergraduate dissertation and the changing nature of the student undertaking it. For many, it will be the first time they will have undertaken a self-directed, major research project. The focus of this paper is to present the neuro-linguistic programming (NLP) framework for setting well-formed outcomes that was offered to students in the initial session of a pilot dissertation workshop support programme, initially targeting students completing dissertation projects on marketing topics within the Business School. Unlike modules on Research Methods the focus of this programme was not on methodology, but on soft skills such as goal setting, time management and motivation, along with practical skills such as those required to take advantage of developments in data processing technology. The paper also presents the findings of qualitative data gathered from responses of students in focus groups and in-depth interviews designed to explore students’ on-going motivation throughout the dissertation process. The paper concludes with a comparison of the results of those students who took part in the workshop sessions with those that did not

Let Me Give You My Card : A Study of Evolving Business Protocols in the Information Age

Non peer reviewedFinal Accepted Versio

Aliens and Others in the Inklings

David Bratman, Janet Brennan Croft, Robin Reid, and John Rosegrant discuss the alien and the Other in the works of the Inklings, with time for audience conversation

Project management maturity in the age of big data

While the area of project management maturity (PMM) is attracting an increased amount of research attention, the approaches to measuring maturity fit within existing social science conventions. This paper aims to examine the potential contribution of new data collection and analytical approaches to develop new insights in PMM. This paper takes the form of a literature review. Findings suggest that the current trends of rapidly growing digital data collection and storage may have the potential to develop approaches to PMM assessment that overcome the limitations of existing qualitative and quantitative approaches

Unequal-mass boson-star binaries: Initial data and merger dynamics

We present a generalization of the curative initial data construction derived for equal-mass compact binaries in Helfer {\it et al} (2019 Phys. Rev. D 99 044046; 2022 Class. Quantum Grav. 39 074001) to arbitrary mass ratios. We demonstrate how these improved initial data avoid substantial spurious artifacts in the collision dynamics of unequal-mass boson-star binaries in the same way as has previously been achieved with the simpler method restricted to the equal-mass case. We employ the improved initial data to explore in detail the impact of phase offsets in the coalescence of equal- and unequal-mass boson star binaries.Comment: 37 pages, 12 figures, to match published version in CQ

The Gravitational Afterglow of Boson Stars

In this work we study the long-lived post-merger gravitational wave signature of a boson-star binary coalescence. We use full numerical relativity to simulate the post-merger and track the gravitational afterglow over an extended period of time. We implement recent innovations for the binary initial data, which significantly reduce spurious initial excitations of the scalar field profiles, as well as a measure for the angular momentum that allows us to track the total momentum of the spatial volume, including the curvature contribution. Crucially, we find the afterglow to last much longer than the spin-down timescale. This prolonged gravitational wave afterglow provides a characteristic signal that may distinguish it from other astrophysical sources.Comment: Movie: https://youtu.be/JE5FRG7kgvU Data: https://github.com/ThomasHelfer/BosonStarAfterglo

Toward a conceptual framework of emotional relationship marketing: an examination of two UK political parties

The purpose of this paper is to review the notion of branding and evaluate its applicability to political parties. As ideological politics is in decline, branding may provide a consistent narrative where voters feel a sense of warmth and belonging. The paper aims to build an understanding of the complexity of building a political brand where a combination of image, logo, leadership, and values can all contribute to a compelling brand narrative. It investigates how competing positive and negative messages attempt to build and distort the brand identity. A critical review of bran ding, relationship marketing, and political science literature articulates the conceptual development of branding and its applicability to political parties. The success or failure of negative campaigning is due to the authenticity of a political party’s brand values — creating a coherent brand story — if there is no distance between the brand values articulated by the political party and the values their community perceives then this creates an "authentic" brand. However, if there is a gap this paper illustrates how negative campaigning can be used to build a "doppelganger brand," which undermines the credibility of the authentic political brand. The paper argues that political parties need to understand how brand stories are developed but also how they can be used to protect against negative advertising. This has implications for political marketing strategists and political parties. This paper draws together branding theory and relationship marketing and incorporates them into a framework that makes a contribution to the political marketing literature

Using ILP to Identify Pathway Activation Patterns in Systems Biology

We show a logical aggregation method that, combined with propositionalization methods, can construct novel structured biological features from gene expression data. We do this to gain understanding of pathway mechanisms, for instance, those associated with a particular disease. We illustrate this method on the task of distinguishing between two types of lung cancer; Squamous Cell Carcinoma (SCC) and Adenocarcinoma (AC). We identify pathway activation patterns in pathways previously implicated in the development of cancers. Our method identified a model with comparable predictive performance to the winning algorithm of a recent challenge, while providing biologically relevant explanations that may be useful to a biologist