OBJECTIVES: To identify the factors that influence the assessment of reported cases of physician-assisted death by members of the public prosecution. DESIGN/SETTING: At the beginning of 1996, during verbal interviews, 12 short case-descriptions were presented to a representative group of 47 members of the public prosecution in the Netherlands. RESULTS: Assessment varied considerably between respondents. Some respondents made more "lenient" assessments than others. Characteristics of the respondents, such as function, personal-life philosophy and age, were not related to the assessment. Case (...) characteristics, i.e. the presence of an explicit request, life expectancy and the type of suffering, strongly influenced the assessment. Of these characteristics, the presence or absence of an explicit request was the most important determinant of the decision whether or not to hold an inquest. CONCLUSIONS: Although the presence of an explicit request, life expectancy and the type of suffering each influenced the assessment, each individual assessment was dependent on the assessor. The resulting danger of legal inequality and legal uncertainty, particularly in complicated cases, should be kept to a minimum by the introduction of some form of protocol and consultation in doubtful or boundary cases. The notification procedure already promotes a certain degree of uniformity in the prosecution policy. (shrink)

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates. BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ’learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the (...) relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system. (shrink)

BackgroundIn research ethics, the most basic question would always be, “which is an ethical issue, which is not?” Interestingly, depending on which ethics guideline we consult, we may have various answers to this question. Though we already have several international ethics guidelines for biomedical research involving human participants, ironically, we do not have a harmonized document which tells us what these various guidelines say and shows us the areas of consensus. In this manuscript, we attempted to do just that.MethodsWe extracted (...) the imperatives from five internationally-known ethics guidelines and took note where the imperatives came from. In doing so, we gathered data on how many guidelines support a specific imperative.ResultsWe found that there is no consensus on the majority of the imperatives and that in only 8.2 % of the imperatives were there at least moderate consensus. Of the 12 clusters, Informed Consent has the highest level of consensus and Research Collaboration and Regulatory Sanctions have the least.ConclusionThere was a lack of consensus in the majority of imperatives from the five internationally-known ethics guidelines. This may be partly explained by the differences among the guidelines in terms of their levels of specification as well as conceptual/ideological differences. (shrink)

As part of the Dutch national science program “Professional Games for Professional Skills” we developed a stress-exposure biofeedback training in virtual reality for the Dutch police. We aim to reduce the acute negative impact of stress on performance, as well as long-term consequences for mental health by facilitating physiological stress regulation during a demanding decision task. Conventional biofeedback applications mainly train physiological regulation at rest. This might limit the transfer of the regulation skills to stressful situations. In contrast, we provide (...) the user with the opportunity to practice breathing regulation while they carry out a complex task in VR. This setting poses challenges from a technical – as well as from a user-experience perspective. We illustrate how we approach these challenges in our training and hope to contribute a useful reference for researchers and developers in academia or industry who are interested in using biosignals to control elements in a dynamic virtual environment. (shrink)

In this article, an ethical analysis of an educational programme on renal replacement therapy options for patients and their social network is presented. The two main spearheads of this approach are: (1) offering an educational programme on all renal replacement therapy options ahead of treatment requirement and (2) a home-based approach involving the family and friends of the patient. Arguments are offered for the ethical justification of this approach by considering the viewpoint of the various stakeholders involved. Finally, reflecting on (...) these ethical considerations, essential conditions for carrying out such a programme are outlined. The goal is to develop an ethically justified and responsible educational programme. (shrink)

It is widely recognized that police performance may be hindered by psychophysiological state changes during acute stress. To address the need for awareness and control of these physiological changes, police academies in many countries have implemented Heart-Rate Variability biofeedback training. Despite these trainings now being widely delivered in classroom setups, they typically lack the arousing action context needed for successful transfer to the operational field, where officers must apply learned skills, particularly when stress levels rise. The study presented here aimed (...) to address this gap by training physiological control skills in an arousing decision-making context. We developed a Virtual-Reality breathing-based biofeedback training in which police officers perform deep and slow diaphragmatic breathing in an engaging game-like action context. This VR game consisted of a selective shoot/don’t shoot game designed to assess response inhibition, an impaired capacity in high arousal situations. Biofeedback was provided based on adherence to a slow breathing pace: the slower and deeper the breathing, the less constrained peripheral vision became, facilitating accurate responses to the in-game demands. A total of nine male police trainers completed 10 sessions over a 4-week period as part of a single-case experimental ABAB study-design. Results showed that eight out of nine participants showed improved breathing control in action, with a positive effect on breathing-induced low frequency HRV, while also improving their in-game behavioral performance. Critically, the breathing-based skill learning transferred to subsequent sessions in which biofeedback was not presented. Importantly, all participants remained highly engaged throughout the training. Altogether, our study showed that our VR environment can be used to train breathing regulation in an arousing and active decision-making context. (shrink)