Social networks, social capital and end-of-life care for people with dementia: a realist review

OBJECTIVES (1) To develop an understanding of how social capital may be conceptualised within the context of endof-life care and how it can influence outcomes for people with dementia and their families with specific reference to the context and mechanisms that explain observed outcomes. (2) To produce guidance for healthcare systems and researchers to better structure and design a public health approach to end-of-life care for people with dementia. DESIGN A realist review. Data sources MEDLINE, EMBASE, CINAHL and grey literature. ANALYSIS We conceptualised social capital as a complex intervention and, in order to understand how change is generated, used realist evaluation methods to create different configurations of context, mechanism and outcomes. We conducted an iterative search focusing on social capital, social networks and end-of-life care in dementia. All study designs and outcomes were screened and analysed to elicit explanations for a range of outcomes identified. Explanations were consolidated into an overarching programme theory that drew on substantive theory from the social sciences and a public health approach to palliative care. RESULTS We identified 118 articles from 16 countries ranging from 1992 to 2018. A total of 40 contextmechanism-outcome configurations help explain how social capital may influence end-of-life care for people with dementia. Such influence was identified within five key areas. These included: (1) socially orientating a person with dementia following diagnosis; (2) transitions in the physical environment of care; (3) how the caregiving experience is viewed by those directly involved with it; (4) transition of a person with dementia into the fourth age; (5) the decision making processes underpinning such processes. CONCLUSION This review contributes to the dispassionate understanding of how complex systems such as community and social capital might be viewed as a tool to improve end-of-life care for people with dementia. PROSPERO REGISTRATION NUMBER CRD42018084524

The ROTSE-III Robotic Telescope System

The observation of a prompt optical flash from GRB990123 convincingly demonstrated the value of autonomous robotic telescope systems. Pursuing a program of rapid follow-up observations of gamma-ray bursts, the Robotic Optical Transient Search Experiment (ROTSE) has developed a next-generation instrument, ROTSE-III, that will continue the search for fast optical transients. The entire system was designed as an economical robotic facility to be installed at remote sites throughout the world. There are seven major system components: optics, optical tube assembly, CCD camera, telescope mount, enclosure, environmental sensing & protection and data acquisition. Each is described in turn in the hope that the techniques developed here will be useful in similar contexts elsewhere.Comment: 19 pages, including 4 figures. To be published in PASP in January, 2003. PASP Number IP02-11

Awareness in severe Alzheimer’s disease: a systematic review

OBJECTIVE: There is limited understanding about how people in the severe stages of Alzheimer’s disease (AD) experience and demonstrate awareness. We synthesised all available evidence with the aim of understanding how awareness is preserved or impaired in severe AD and what evidence there is for different levels of awareness according to the levels of awareness framework. METHOD: A systematic search of the following databases: Embase, PsycINFO, MEDLINE and Web of Science was carried out. A narrative synthesis and analysis was conducted of all included studies. All studies were assessed for quality using the AXIS and CASP tools. RESULTS: Our findings suggest that lower level sensory awareness is relatively maintained in severe AD. Findings for higher level awareness are variable and this may be related to the diversity of methods that have been used to explore awareness in these circumstances. CONCLUSION: Awareness is complex, heterogeneous and varies significantly between individuals. Environmental and contextual factors have a significant impact on whether awareness is observed in people with severe AD. Adaptation of the environment has the potential to facilitate the expression of awareness while education of caregivers may increase understanding of people with severe AD and potentially improve the quality of care that is received

Utilización de modelos de reflectancia como nexo entre muestras foliares y la cobertura forestal: aplicación a datos hiperespectrales

[ES] El presente trabajo demuestra la utilización de modelos de simulación de la cobertura forestal mediante su aplicación a datos hiperespectrales del sensor aerotransportado CASI. Los modelos SAIL y Kuusk permiten ser utilizados como nexo de unión entre los niveles de hoja y de cobertura: las relaciones a nivel de hoja obtenidas entre índices ópticos y bioindicadores de estrés, como contenido clorofílico o fluorescencia clorofílica, pueden ser transformadas a un nivel superior de cobertura mediante la utilización de dichos modelos. Finalmente se realiza una demostración de la utilización de modelos de cobertura a través de los resultados obtenidos en el proyecto Bioindicators of Forest Sustainability, desarrollado en 12 zonas de Acer saccharum M. localizadas en Ontario (Canadá) donde se obtuvieron medidas de campo de muestras foliares, así como datos hiperespectrales del sensor aerotransportado CASI en 1997, 1998 y 1999. Los indices ópticos desarrollados a nivel de hoja fueron aplicados, a través de modelos de cobertura, a los datos de reflectancia obtenidos por CASI de 2 m de resolución espacial y 72 bandas[EN] This paper demonstrates the use and applications of Canopy Reflectance Models (CR) with airborne hyperspectral CASI data. SAIL and Kuusk canopy reflectance models are the link between the leaf and canopy levels: leaf-level relationships obtained between optical indices and stress bioindicators, such as chlorophyll content and chlorophyll fluorescence can be scaled-up to the canopy level using canopy reflectance models. The application of canopy reflectance models is demonstrated with the results obtained in the Bioindicators of Forest Sustainability Project. The work was carried out in 12 study areas of Acer saccharum M. in the Algoma Region, Ontario (Canada), where field measurements and hyperspectral CASI imagery have been collected in 1997, 1998 and 1999 deployments. Single leaf reflectance and transmittance, chlorophyll and carotenoid content, and chlorophyll fluorescence of broad leaves were measured. The physiological indices and derivative analysis indices extracted from leaf spectral reflectance were tested at canopy level using CASI data of 72 channels and 2 m spatial resolution.Peer reviewe

Muscle Activated 3D Printed Prosthetic Arm

Due to the rapid growth of children and the cost of myoelectric technology, children are not given the same opportunities to use myoelectric prosthetics as adults. The Muscle Activated Prosthesis (MAP) team seeks to reconcile this by creating an affordable, trans-radial, myoelectric prosthesis that utilizes the flexibility of 3D printing technology for a fourteen-year-old congenital amputee named Lily. The MAP team has completed the design and prototype of a myoelectric prosthesis with a material cost of approximately $1,000 as opposed to the$10,000-$20,000 cost of clinically accepted myoelectric prosthetic upper limbs. The 3D printed prosthetic arm prototype incorporates electromyography (EMG) electrodes, a motor and tendon system, an open-source prosthetic hand design, a custom printed circuit board (PCB), and lithium-ion battery power. The opening and closing of the prosthetic hand is controlled by the myoelectric signals from the user’s forearm contractions which can be tested by the team using our adaptive prosthetic attachment. All these components result in an affordable prosthetic that has the potential for customization and adaptation to different sized limbs. Funding for this work provided by The Collaboratory for Strategic Partnerships and Applied Research.https://mosaic.messiah.edu/engr2022/1009/thumbnail.jp

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded