Agitation and impulsivity in mid and late life as possible risk markers for incident dementia

To identify knowledge gaps regarding new-onset agitation and impulsivity prior to onset of cognitive impairment or dementia the International Society to Advance Alzheimer's Research and Treatment Neuropsychiatric Syndromes (NPS) Professional Interest Area conducted a scoping review. Extending a series of reviews exploring the pre-dementia risk syndrome Mild Behavioral Impairment (MBI), we focused on late-onset agitation and impulsivity (the MBI impulse dyscontrol domain) and risk of incident cognitive decline and dementia. This scoping review of agitation and impulsivity pre-dementia syndromes summarizes the current biomedical literature in terms of epidemiology, diagnosis and measurement, neurobiology, neuroimaging, biomarkers, course and prognosis, treatment, and ongoing clinical trials. Validations for pre-dementia scales such as the MBI Checklist, and incorporation into longitudinal and intervention trials, are needed to better understand impulse dyscontrol as a risk factor for mild cognitive impairment and dementia.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.Daniel Bateman receives support from the Indiana University Richard M. Fairbanks Chair of Aging Research, the Indiana University Cornelius and Yvonne Pettinga Chair of Medicine, and funding from the National Institute on Aging (NIA) grants K23AG059914 and P30AF10133. Sascha Gill receives funding from a University of Calgary Graduate Student Research Award. Sophie Hu receives funding from a Cana dian Institute of Health Research (CIHR) Master’s Research Award. Erin Foster: none. Myuri Ruthirakuhan receives funding from a CIHR Doctoral Research Award. Allis Sellek receives funding from Alzheimer Foundation of Costa Rica. Moyra Mortby receives support from the Australian National Health and Medical Research Council (NHMRC) and Australian Research Council (ARC) Dementia Research Development Fellowship #1102028. Veronika Matušková receives support from MH CZ – DRO, Motol University Hospital, Prague, Czech Republic 00064203 and Czech Ministry of Health grant 16-27611A. Kok Pin Ng: none. Rawan Tarawneh receives support from the Ohio State University Chronic Brain Injury Discovery Themes. Yvonne Freund-Levi:none. Sanjeev Kumar receives research support from Brain and Behavior Foundation, National institute on Ageing, BrightFocus Foundation, Brain Canada, Canadian Institute of Health Research, Centre for Ageing and Brain Health Innovation, Weston Brain Institute, and Centre for Mental Health and Addiction Foundation and University of Toronto. Serge Gauthier receives support from the CIHR, Weston, and the National Institutes of Health (NIH). Paul Rosenberg receives funding from the National Institute on Aging (NIA) grants R01AG049872 and R01 AG054771. Fabricio Ferreira de Oliveira has a grant from FAPESP - The State of São Paulo Research Foundation (grant #2015/10109-5). Devangere Devanand: none. Clive Ballard: none. Zahinoor Ismail has received funding from Alzheimer’s Society of Calgary via the Hotchkiss Brain Institute.published version, accepted version (12 month embargo), submitted versio

Smart-retrofitting of existing buildings by predictive calculation of heating load using non-destructive testing

The construction sector is one of the most resource-intensive sectors and responsible for a considerable share of energy consumption & greenhouse gas emissions. Specifically, the maintenance phase of a building’s lifecycle has become the focus of attention, as old buildings consume an enormous amount of energy and result in tremendous detrimental impacts on the environment. Recent advancements in building information modelling and simulating building energy performance have provided opportunities for energy optimization. While energy simulation can be applied as a tool to evaluate the energy performance of a building in operation, the emergence of BIM technology facilitates the evaluation process with predefined and enriched building information. Although with current sensor technologies existing buildings can be represented digitally, they fail to describe the structure of each building element separately. This paper proposes a methodology to detect and identify additional information of each building element required to perform reliable energy simulation. A new age portable radar is used to probe building elements and predict their thermal transmittance to in-turn optimize for heating energy by appropriately retrofitting the structures. The methodology is tested on prototype elements built to mimic existing buildings and the simulations are carried out on a commercially available building planning software