There are currently about 6 million – mainly older – people with dementia in the European Union. With ageing, a number of sensory changes occur. Dementia syndrome exacerbates the effects of these sensory changes and alters perception of stimuli. People with dementia have an altered sensitivity for indoor environmental conditions, which can induce problematic behaviour with burdensome symptoms to both the person with dementia and the family carer. This paper, based on literature review, provides an overview of the indoor environmental parameters, as well as the integrated design and implementation of relevant building systems. The overview is presented in relation to the intrinsic ageing of senses, the responses of older people with dementia and the impact on other relevant stakeholders through the combined use of the International Classification of Functioning, Disability and Health, and the Model of Integrated Building Design. Results are presented as indicators of the basic value, functional value and economic value, as well as a synthesis of building-related solutions. Results can help designers and building services engineers to create optimal environmental conditions inside the living environments for people with dementia, and can be used to raise awareness among health care professionals about of the influence of the indoor environment on behaviour of the person with dementia.
Student burnout is raising an increasing amount of concern. Burnout often leads to psychosocial problems and drop-out. In this study multiple regression analysis was used to examine the impact of performance pressure, loneliness, and sense of belonging on the underlying dimensions of burnout in 3,134 university students in the Netherlands. Results suggest that sense of belonging could be targeted as a way to enhance student wellbeing, in order to improve the ability to cope with the high demands in student life and the prevention of burnout.
Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
