The Role of Donated Labour and Not for Profit at the Public/Private Interface

The aim of this paper is to assess the role of donated labour and not-for-profit (NFP) entities at the public private interface. After discussing what a NFP enterprise is and providing general background, we look at the underlying theory of NFP institutions. The fact that NFP companies are able to precommit themselves not to expropriate donated labour is identified as a primary justification of the NFP model and we emphasise the role that purchasers play in the expropriation problem and suggest that this is a particular concern for institutions at the public private interface. After summarising the empirical literature we provide a brief case study of Glas Cymru and show that it is likely to fall foul of the purchaser problems in that the structure makes it hard to avoid expropriation of donated labour. Although there is limited empirical evidence investigation of what is available suggests that the shift from FP to NFP has had no significant effect on the company. Finally, we address the issue of Foundation Hospitals and suggest that there is more, albeit limited, reason to suggest that the NFP status will prove beneficial for donating labour.not-for-profit, public private interface

The influence of a challenge course based pre-orientation\u27s curriculum integration on participants\u27 perceived self-efficacy

This present work employed a quasi-experimental study to examine the change of college and academic self-efficacy perception of first year students following their experience upon participation in a Challenge Course Based Orientation Program (CCBOP) covering varying levels of University 101 curriculum integration. In total 68 first year students out of an available 96 participated in the study. Four individual programs were chosen, two were randomly assigned a \u27Holistically integrated\u27 treatment (n=37) and the remaining programs were assigned \u27Non-integrated\u27 treatment (n=31). All participants completed the College Self-Efficacy Inventory (CSEI), and College Academic Self-Efficacy Scale (CASES) prior to and immediately following the CCBOP experience.;Measurement of differences between pre-test and post-test values of both instruments by total response as well as by treatment groups was made. Non biased analysis of the CBOP\u27s effect upon student treatment groups was examined via determination of effect size. Mean gain score of treatment groups pre-test/post-test differences were compared via independent t-test to identify significant differences.;Results show significant increase in students\u27 self-efficacy perception among both treatment groups on items within the CSEI and produced \u27moderate\u27 to \u27large\u27 effect sizes. \u27Integrated\u27 treatment responses generated a greater number of items of significant difference within the CASES when compared to the \u27Non-integrated\u27 treatment group. \u27Integrated\u27 treatment results show a high majority of \u27large\u27 effect sizes highlighting the treatments ability to influence participants\u27 perceived college self-efficacy

Finding Optimal Solutions to Backbone Minimisation Problems using Mixed Integer Programming

Attempts to evaluate heuristic algorithms are often hampered by the lack of known exact solutions with which to compare results. This is true, in particular, in the study of network backbone design - to date, a fairly undeveloped area in mathematical optimisation. This paper uses a Mixed Integer Programming (MIP) approach to find optimal solutions to the problem of backbone minimisation in mesh networks. A simple model is formulated and then adapted to reduce the number of variables and constraints. Network reliability issues are then considered and a more complex model introduced. Finally the model is solved using a commercial solver to generate test instances with which to test the accuracy of a simulated annealing (SA) heuristic. The heuristic is shown to be accurate to within a very small error margin and the strengths and weaknesses of the two approaches are discussed

Spanning Tree Objective Functions and Algorithms for Wireless Networks

This paper considers various forms of objective function that may be applied in the calculation of spanning trees in different network situations. Conventional link and path cost approaches are compared to those based on switch or bridge costs more appropriate for wireless applications. Variant objectives are formulated and compared. Although efficient exact algorithmic approaches exist only for the link cost objectives, reasonable approximations for the switch/bridge equivalents are to be found with simple greedy heuristics and better results still through various forms of iterated local search such as tabu search and simulated annealing

Optimisation Techniques for Wireless Networks

This paper introduces two new algorithms for the minimum connected dominating set problem. The problem and its relevance to various aspects of wireless network optimisation are briefly outlined followed by a description of the suggested techniques. Results show that these algorithms outperform a number of previous approaches in terms of solution quality and potential for future work is discussed

Adaptable and Collaborative Virtual Learning Environments Supporting Soft Skills

The adaptation of virtual learning environments (VLEs) into academic and business cultures has increasingly become a dominant factor in their operation. Often seen as avenues providing flexible solutions and attributing to new approaches in maintaining and applying learning opportunities, the implementation of e-learning has the potential to provide new approaches to satisfy the requirements of learning. However this powerful tool introduces an avalanche of ethical and social aspects to contend with. An incentive for the deployment of these environments is the promise of advancements provided through technology, such as improved usability and communication. There should be focuses on both the ethical and social aspects to deploying an educational community. Although their application is usually in a supportive role, alongside conventional teaching practices, the additional resources to maintain these environments can sometimes outweigh practicality and be limited when utilised. These environments should be seen as the opportunity to manifest wisdom and skill through innovative approaches and provide participants with efficient methods to self-reflect via each other. Are advancements in technology truly producing innovative and unconventional approaches, which provide a seamless transition from conventional classroom teaching? This paper examines the problems associated with the deployment of virtual learning environments to sustain knowledge through collaborative and adaptable learning and focuses on the problems associated with supporting soft skills online

Search for direct production of charginos, neutralinos and sleptons in final states with two leptons and missing transverse momentum in pp collisions at √s = 8TeV with the ATLAS detector

Searches for the electroweak production of charginos, neutralinos and sleptons in final states characterized by the presence of two leptons (electrons and muons) and missing transverse momentum are performed using 20.3 fb−1 of proton-proton collision data at s√ = 8 TeV recorded with the ATLAS experiment at the Large Hadron Collider. No significant excess beyond Standard Model expectations is observed. Limits are set on the masses of the lightest chargino, next-to-lightest neutralino and sleptons for different lightest-neutralino mass hypotheses in simplified models. Results are also interpreted in various scenarios of the phenomenological Minimal Supersymmetric Standard Model

Evaluation of Twitter data for an emerging crisis: an application to the first wave of COVID-19 in the UK

In the absence of nationwide mass testing for an emerging health crisis, alternative approaches could provide necessary information efficiently to aid policy makers and health bodies when dealing with a pandemic. The following work presents a methodology by which Twitter data surrounding the first wave of the COVID-19 pandemic in the UK is harvested and analysed using two main approaches. The first is an investigation into localized outbreak predictions by developing a prototype early-warning system using the distribution of total tweet volume. The temporal lag between the rises in the number of COVID-19 related tweets and officially reported deaths by Public Health England (PHE) is observed to be 6–27 days for various UK cities which matches the temporal lag values found in the literature. To better understand the topics of discussion and attitudes of people surrounding the pandemic, the second approach is an in-depth behavioural analysis assessing the public opinion and response to government policies such as the introduction of face-coverings. Using topic modelling, nine distinct topics are identified within the corpus of COVID-19 tweets, of which the themes ranged from retail to government bodies. Sentiment analysis on a subset of mask related tweets revealed sentiment spikes corresponding to major news and announcements. A Named Entity Recognition (NER) algorithm is trained and applied in a semi-supervised manner to recognise tweets containing location keywords within the unlabelled corpus and achieved a precision of 81.6%. Overall, these approaches allowed extraction of temporal trends relating to PHE case numbers, popular locations in relation to the use of face-coverings, and attitudes towards face-coverings, vaccines and the national ‘Test and Trace’ scheme