Rights, Rationality and Reproduction: Balancing Interests in the Abortion Debate

As medical technology has advanced, so too have our attitudes towards the level of control we can or should expect to have over our procreative capacities. This creates a multidimensional problem for the law and family planning services in terms of access to services – whether to avoid conception or terminate a pregnancy – and the negligent provision of these services. These developments go to the heart of our perception of autonomy. Unsurprisingly, these matters also raise a moral dilemma for the law. Distinctively, discourse in this area is dominated by assertions of subjective moral value; in relation to life, to personal choice and to notions of the archetypal family. Against this, I stress that a model of objective morality can answer these challenging questions and resolve the inherent problems of legal regulation. Therefore, I argue that notions of autonomy must be based on a rational, action-based understanding of what it means to be a ‘moral agent’. I claim that from this we might support a legal standard, based on objective rational morality, which can frame our constitutional norms and our conception of justice in these contentious areas. This paper claims that the current regulation of abortion is outdated and requires radical reform. It proposes a scheme that would shift the choice towards the mother (and the father), remove the unnecessarily broad disability ground and involve doctors having a role of counsel (rather than gatekeeper).

Literature Review WM9: Part II - light goods vehicles in urban areas, carried as as part Work Module 1, Green Logistics Project

LGVs are of ever-greater importance in terms of the final delivery of many time-critical, high value goods and are also widely used in industries that provide a wide range of critical support services. There are almost five times as many LGVs as there are HGVs (goods vehicles over 3.5 tonnes gross vehicle weight) currently licensed in Britain. The LGV fleet in Britain is growing at a faster rate than the HGV fleet, and the LGV fleet travels more than twice as many vehicle kilometres each year than the total HGV fleet. LGVs perform a far greater proportion of their total distance travelled in urban areas than HGVs, and consume 25% of the total diesel and 3% of the total petrol used by all motorised road transport vehicles in Britain.

A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Probation staff experiences of managing suicidal and self-harming service users.

The current study sought to explore the impact of suicidal behaviours on probation staff, in relation to their experiences of working with probation service users who have carried out suicide, attempted suicide or self-harm. Thirteen in-depth interviews were carried out with probation staff who had direct contact with probation service users in one probation area, and had varying degrees of experience of managing suicidal or self-injurious service users. These were analysed using thematic analysis and five themes were identified. Findings indicate that staff felt that suicide and self-harm by service users are serious issues which need to be recognized and dealt with in an effective yet compassionate manner. Not attending the suicide prevention training, or lack of experience, were perceived as restricting their ability to know how to deal with these individuals, and offer support. Furthermore, staff were emotionally affected by these incidents and it is recommended that they should continue to be provided with access to appropriate support services after an incident.

From science gateways to commercial solutions

The European CloudSME project that incorporated 24 European SMEs, besides five academic partners, has finished its funded phase in March 2016. This presentation will provide a summary of the results of the project, and will analyze the challenges and differences when developing “SME Gateways”, when compared to “Science Gateways”. CloudSME started in 2013 with the aim to develop a cloud-based simulation platform for manufacturing and engineering SMEs. The project was based around industry use-cases, five of which were incorporated in the project from the start, and seven additional ones that were added as an outcome of an open call in January 2015. CloudSME utilized science gateway related technologies, such as the commercial CloudBroker Platform and the WS-PGRADE/gUSE Gateway Framework that were developed in the preceding SCI-BUS project. As most important outcome, the project successfully implemented 12 industry quality demonstrators that showcase how SMEs in the manufacturing and engineering sector can utilize cloud-based simulation services. Some of these solutions are already market-ready and currently being rolled out by the software vendor companies. Some others require further fine-tuning and the implementation of commercial interfaces before being put into the market. The CloudSME use-cases came from a very wide application spectrum. The project implemented, for example, an open marketplace for micro-breweries to optimize their production and distribution processes, an insole design validation service to be used by podiatrists and shoe manufacturers, a generic stock management solution for manufacturing SMEs, and also several “classical” high-performance computing case-studies, such as fluid dynamics simulations for model helicopter design, and dual-fuel internal combustion engine simulation. As the project generated significant impact and interest in the manufacturing sector, 10 CloudSME stakeholders established a follow-up company called CloudSME UG for the future commercialization of the results. Besides the success stories, this talk would also like to highlight the difficulties when transferring the outcomes of an academic research project to real commercial applications. The different mindset and approach of academic and industry partners presented a real challenge for the CloudSME project, with some interesting and valuable lessons learnt. The academic way of supporting SMEs did not always work well with the rather different working practices and culture of many participants. Also, the quality of support regarding operational solutions required by the SMEs is well beyond the typical support services academic institutions are prepared for. Finally, a clear lack of trust in academic solutions when compared to commercial solutions was also imminent. The talk will highlight some of these challenges underpinned by the implementation of the CloudSME use-cases.