48 research outputs found

    Concert recording 2021-11-07a

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    [Track 1]. La maniere de Shumann /Jean-Michel Defaye -- [Track 2]. Sang till lotta / Jan Sandstrom -- [Track 3]. Concertino in Bā™­ / Ernst Sachse -- [Track 4]. Nearer my God to thee for 9 celli / James Stevens -- [Track 5]. Ave Maria / Franz Biebl -- [Track 6]. Soundtrack for trombone / Brian Sadler

    Macrophyte abundance in Waquoit Bay : effects of land-derived nitrogen loads on seasonal and multi-year biomass patterns

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    Author Posting. Ā© The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Estuaries and Coasts 31 (2008): 532-541, doi:10.1007/s12237-008-9039-6.Anthropogenic inputs of nutrients to coastal waters have rapidly restructured coastal ecosystems. To examine the response of macrophyte communities to land-derived nitrogen loading, we measured macrophyte biomass monthly for six years in three estuaries subject to different nitrogen loads owing to different land uses on the watersheds. The set of estuaries sampled had nitrogen loads over the broad range of 12 to 601 kg N ha-1 y-1. Macrophyte biomass increased as nitrogen loads increased, but the response of individual taxa varied. Specifically, biomass of Cladophora vagabunda and Gracilaria tikvahiae increased significantly as nitrogen loads increased. The biomass of other macroalgal taxa tended to decrease with increasing load, and the relative proportion of these taxa to total macrophyte biomass also decreased. The seagrass, Zostera marina, disappeared from the higher loaded estuaries, but remained abundant in the estuary with the lowest load. Seasonal changes in macroalgal standing stock were also affected by nitrogen load, with larger fluctuations in biomass across the year and higher minimum biomass of macroalgae in the higher loaded estuaries. There were no significant changes in macrophyte biomass over the six years of this study, but there was a slight trend of increasing macroalgal biomass in the latter years. Macroalgal biomass was not related to irradiance or temperature, but Z. marina biomass was highest during the summer months when light and temperatures peak. Irradiance might, however, be a secondary limiting factor controlling macroalgal biomass in the higher loaded estuaries by restricting the depth of the macroalgal canopy. The relationship between the bloom-forming macroalgal species, C. vagabunda and G. tikvahiae, and nitrogen loads suggested a strong connection between development on watersheds and macroalgal blooms and loss of seagrasses. The influence of watershed land uses largely overwhelmed seasonal and inter-annual differences in standing stock of macrophytes in these temperate estuaries.This research was supported by the National Oceanic and Atmospheric Administration (NOAA), Cooperative Institute for Coastal and Estuarine Environmental Technologies (CICEET-UNH#99-304, NOAA NA87OR512), NOAA National Estuarine Research Reserve Graduate Research Fellowship NERRS GRF, #NA77OR0228), and an Environmental Protection Agency (EPA) STAR Fellowship for Graduate Environmental Study (U-915335-01-0) awarded to J. Hauxwell. S. Fox was supported by a NOAA NERRS GRF (#NA03NOS4200132) and an EPA STAR Graduate Research Fellowship. We also thank the Quebec-Labrador Foundation Atlantic Center for the Environment's Sounds Conservancy Program and the Boston University Ablon/Bay Committee for their awarding research funds

    Comparing Dutch Case management care models for people with dementia and their caregivers: The design of the COMPAS study

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    <p>Abstract</p> <p>Background</p> <p>Dementia care in the Netherlands is shifting from fragmented, ad hoc care to more coordinated and personalised care. Case management contributes to this shift. The linkage model and a combination of intensive case management and joint agency care models were selected based on their emerging prominence in the Netherlands. It is unclear if these different forms of case management are more effective than usual care in improving or preserving the functioning and well-being at the patient and caregiver level and at the societal cost. The objective of this article is to describe the design of a study comparing these two case management care models against usual care. Clinical and cost outcomes are investigated while care processes and the facilitators and barriers for implementation of these models are considered.</p> <p>Design</p> <p>Mixed methods include a prospective, observational, controlled, cohort study among persons with dementia and their primary informal caregiver in regions of the Netherlands with and without case management including a qualitative process evaluation. Inclusion criteria for the cohort study are: community-dwelling individuals with a dementia diagnosis who are not terminally-ill or anticipate admission to a nursing home within 6ā€‰months and with an informal caregiver who speaks fluent Dutch. Person with dementia-informal caregiver dyads are followed for two years. The primary outcome measure is the Neuropsychiatric Inventory for the people with dementia and the General Health Questionnaire for their caregivers. Secondary outcomes include: quality of life and needs assessment in both persons with dementia and caregivers, activity of daily living, competence of care, and number of crises. Costs are measured from a societal perspective using cost diaries. Process indicators measure the quality of care from the participantā€™s perspective. The qualitative study uses purposive sampling methods to ensure a wide variation of respondents. Semi-structured interviews with stakeholders based on the theoretical model of adaptive implementation are planned.</p> <p>Discussion</p> <p>This study provides relevant insights into care processes, description of two case management models along with clinical and economic data from persons with dementia and caregivers to clarify important differences in two case management care models compared to usual care.</p

    Linking Symptom Inventories using Semantic Textual Similarity

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    An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment
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