The British public's perception of the UK smart metering initiative: Threats and opportunities

Consumer acceptance of smart meters remains crucial in achieving the potential carbon emission reductions offered by advanced metering infrastructures. Given this, the present research used deliberative focus groups to examine what is needed to secure acceptance and engagement from domestic consumers with services, products and 'offers' in smarter power systems. Our findings suggest that consumers are able to identify not just threats relating to smart metering initiatives but opportunities as well. In particular, our focus group participants responded positively to the idea of an automated system that could be used to achieve energy savings in combination with time-of-use tariffs. We conclude by outlining suggestions for policy recommendations that may help consumer acceptance of smart meter enabled services be more readily achieved

Money doesn’t matter! Householders’ intentions to reduce standby power are unaffected by personalised pecuniary feedback

Many researchers have examined whether giving people feedback about their energy use can lead them to decrease it. However, to date no consensus has been reached about which type of eco-feedback is the most effective. We aim to test the efficacy of different feedback techniques by providing participants with personalised information about the annual monetary costs of their home’s standby power usage (i.e., appliances that consume electricity despite not being actively used). Using a sample of 708 participants we tested the following feedback strategies: advice, disaggregation, loss vs gain framing, social norms, and collective information. We measured the impact of each of these feedback conditions on knowledge and intention to change behaviour, and compared them to a control condition. Using both frequentist and Bayesian analyses, we found that relative to the control condition all the feedback strategies led participants to report significant gains in knowledge. Yet, neither the additional knowledge gains, nor the feedback approach used significantly affected behavioural intentions. Consequently, the results suggest that while a wide range of feedback strategies emphasizing the financial impact of standby power consumption can effectively improve knowledge, this approach alone is insufficient in inciting intentions to change energy consumption behaviours

Consumer sleep monitors: is there a baby in the bathwater?

The rapid expansion of consumer sleep devices is outpacing the validation data necessary to assess the potential use of these devices in clinical and research settings. Common sleep monitoring devices utilize a variety of sensors to track movement as well as cardiac and respiratory physiology. The variety of sensors and user-specific factors offer the potential, at least theoretically, for clinically relevant information. We describe the current challenges for interpretation of consumer sleep monitoring data, since the devices are mainly used in non-medical contexts (consumer use) although medically-definable sleep disorders may commonly occur in this setting. A framework for addressing questions of how certain devices might be useful is offered. We suggest that multistage validation efforts are crucially needed, from the level of sensor data and algorithm output, to extrapolations beyond healthy adults and into other populations and real-world environments

Who should decide how limited healthcare resources are prioritized? Autonomous technology as a compelling alternative to humans

Who should decide how limited resources are prioritized? We ask this question in a healthcare context where patients must be prioritized according to their need and where advances in autonomous artificial intelligence-based technology offer a compelling alternative to decisions by humans. Qualitative (Study 1a; N = 50) and quantitative (Study 1b; N = 800) analysis identified agency, emotional experience, bias-free, and error-free as four main qualities describing people’s perceptions of autonomous computer programs (ACPs) and human staff members (HSMs). Yet, the qualities were not perceived to be possessed equally by HSMs and ACPs. HSMs were endorsed with human qualities of agency and emotional experience, whereas ACPs were perceived as more capable than HSMs of bias- and error-free decision-making. Consequently, better than average (Study 2; N = 371), or relatively better (Studies 3, N = 181; & 4, N = 378), ACP performance, especially on qualities characteristic of ACPs, was sufficient to reverse preferences to favor ACPs over HSMs as the decision makers for how limited healthcare resources should be prioritized. Our findings serve a practical purpose regarding potential barriers to public acceptance of technology, and have theoretical value for our understanding of perceptions of autonomous technologies

Dimethyl fumarate induced lymphopenia in multiple sclerosis: A review of the literature

Dimethyl fumarate (DMF) is a first line medication for multiple sclerosis. It has a favourable safety profile, however, there is concern regarding the occurrence of moderate-severe and sustained lymphopenia and the associated risk of progressive multifocal leukoencephalopathy. We carried out an extensive literature review to understand the molecular mechanisms underlying this adverse reaction. Dynamic changes in certain components of the immune system are likely to be important for the therapeutic effects of DMF, including depletion of memory T cells and decrease in activated T cells together with expansion of na\uefve T cells. Similar modifications were reported for the B cell components. CD8+ T cells are particularly susceptible to DMF-induced cell death, with marked reductions observed in lymphopenic subjects. The reasons underlying such increased sensitivity are not known, nor it is known how expansion of other lymphocyte subsets occurs. Understanding the molecular mechanisms underlying DMF action is challenging: in vivo DMF is rapidly metabolized to monomethyl fumarate (MMF), a less potent immunomodulator in vitro. Pharmacokinetics indicate that MMF is the main active species in vivo. However, the relative importance of DMF and MMF in toxicity remains unclear, with evidence presented in favour of either of the compounds as toxic species. Pharmacogenetic studies to identify genetic predictors of DMF-induced lymphopenia are limited, with inconclusive results. A role of the gut microbiome in the pharmacological effects of DMF is emerging. It is clear that further investigations are necessary to understand the mechanisms of DMF-induced lymphopenia and devise preventive strategies. Periodic monitoring of absolute lymphocyte counts, currently performed in clinical practise, allows for the early detection of lymphopenia as a risk-minimization strategy

Who tugs at our heart strings? The effect of avatar images on player generosity in the dictator game.

The present research was motivated by a prior study, where several wallets, each containing a photo of either a baby, a puppy, a family, or an elderly couple, were scattered across a city in the United Kingdom (Wiseman, 2009). Most of the wallets containing a photo of a baby were returned compared to less than a third of wallets containing a photo of an elderly couple. To investigate further, in a series of three studies we examined, using a pseudo online version of the dictator game, possible subtle cues supporting prosocial behaviour by manipulating the type of avatar used by the recipient of the donation made by the 'dictator'. Overall, it emerged that participants showed significantly higher levels of generosity towards babies, and older people, supporting the notion that perceptions of vulnerability and need drive prosocial behaviour

Big data in sleep medicine: prospects and pitfalls in phenotyping

Clinical polysomnography (PSG) databases are a rich resource in the era of “big data” analytics. We explore the uses and potential pitfalls of clinical data mining of PSG using statistical principles and analysis of clinical data from our sleep center. We performed retrospective analysis of self-reported and objective PSG data from adults who underwent overnight PSG (diagnostic tests, n=1835). Self-reported symptoms overlapped markedly between the two most common categories, insomnia and sleep apnea, with the majority reporting symptoms of both disorders. Standard clinical metrics routinely reported on objective data were analyzed for basic properties (missing values, distributions), pairwise correlations, and descriptive phenotyping. Of 41 continuous variables, including clinical and PSG derived, none passed testing for normality. Objective findings of sleep apnea and periodic limb movements were common, with 51% having an apnea–hypopnea index (AHI) >5 per hour and 25% having a leg movement index >15 per hour. Different visualization methods are shown for common variables to explore population distributions. Phenotyping methods based on clinical databases are discussed for sleep architecture, sleep apnea, and insomnia. Inferential pitfalls are discussed using the current dataset and case examples from the literature. The increasing availability of clinical databases for large-scale analytics holds important promise in sleep medicine, especially as it becomes increasingly important to demonstrate the utility of clinical testing methods in management of sleep disorders. Awareness of the strengths, as well as caution regarding the limitations, will maximize the productive use of big data analytics in sleep medicine

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer\u27s disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual\u27s brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD