229 research outputs found

    MILP Model for Energy Supply Design to overcome the Cannibalization of Solar Thermal Plants and large-scale Heat Pumps in Urban District Heating Systems

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    Urban infrastructure is accountable for a large share of carbon emissions, especially energy supply to meet the demand for thermal heat and domestic water. Regarding the climate agreements these systems have to be decarbonized. In urban neighbourhoods, district heating systems (DHS) are efficient solutions to supply heat and favoured by locally or regionally operating municipal utilities. To integrate renewable heat from solar thermal plants or waste heat from lakes or rivers by using heat pumps, DHS in highly densed agglomerations face major problems. On the one hand the availability of land respectively free space is limited. On the other hand operating times of solar thermal plants and large-scale heat pumps are similar considering a long-term planning horizon. In this contribution a mixed integer linear programming (MILP) model is developed todetermine the implementation of both options solar thermal plants as well as large-scale heat pumps in DHS with adjustable generation plants in an optimal way. The model computes minimal investment costs and related emission savings for different alternatives integrating heat of renewable sources. The results can support the decision-making regarding the feasibility. Furthermore, good combinations of different renewable energy sources and their integration into a DHS can be identified even though the sources are distributed over the DHS. Main decision variables are the choice of possible plant sizes under consideration of the (existing) DHS-network layout and available space in highly densed urban districts. The networktopology as well as energetic and ecological constraints (e.g. maximum flow capacity in pipes or operating times of heat pumps due to boundary conditions of heat sources) lead to a selection of plant combinations which represent the optimal solution to lower the emissions at acceptable investment costs. The developed model is applied to a case study for an DHS in a newly built neighbourhood with several available heatsources for heat pumps and free areas for solar thermal collectors. The results proof the function of the model and illustrate that an energetic improvement of the DHS is possible by integrating solar thermal plants and large-scale heat pumps at economically acceptable conditions

    The effect of augmented speech-language therapy delivered by telerehabilitation on post stroke aphasia – a pilot randomized controlled trial

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    Pilot a definitive randomized controlled trial of speech-language telerehabilitation in poststroke aphasia in addition to usual care with regard to recruitment, drop-outs, and language effects. Pilot single-blinded randomized controlled trial. Telerehabilitation delivered from tertiary rehabilitation center to participants at their home or admitted to secondary rehabilitation centers. People with naming impairment due to aphasia following stroke. Sixty-two participants randomly allocated to 5 hours of speech and language telerehabilitation by videoconference per week over four consecutive weeks together with usual care or usual care alone. The telerehabilitation targeted functional, expressive language. Main measures: Norwegian Basic Aphasia Assessment: naming (primary outcome), repetition, and auditory comprehension subtests; Verb and Sentence Test sentence production subtest and the Communicative Effectiveness Index at baseline, four weeks, and four months postrandomization. Data were analyzed by intention to treat. No significant between-group differences were seen in naming or auditory comprehension in the Norwegian Basic Aphasia Assessment at four weeks and four months post randomization. The telerehabilitation group ( n = 29) achieved a Norwegian Basic Aphasia Assessment repetition score of 8.9 points higher ( P = 0.026) and a Verb and Sentence Test score 3 points higher ( P = 0.002) than the control group ( n = 27) four months postrandomization. Communicative Effectiveness Index was not significantly different between groups, but increased significantly within both groups. No adverse events were reported. Augmented telerehabilitation via videoconference may be a viable rehabilitation model for aphasia affecting language outcomes poststroke. A definitive trial with 230 participants is needed to confirm results

    Impact of White Matter Lesions on Cognition in Stroke Patients Free from Pre-Stroke Cognitive Impairment: A One-Year Follow-Up Study

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    Background/Aim: Post-stroke cognitive impairment and dementia may be caused by pure vascular, pure degenerative or mixed disease. The relation between post-stroke cognitive impairment and the combination of vascular pathology and degenerative changes is less evaluated. We aimed to evaluate the associations between white matter lesions (WMLs) and patient performance 1 year after stroke on tests of executive functioning, memory and visuospatial function, adjusted for the effects of lifestyle and disease-related factors, including medial temporal lobe atrophy (MTLA). Methods: Patients with a first-ever stroke or transient ischemic attack were invited to participate in the study. The associations between the cognitive test performances and WMLs were studied using linear regression [Trail Making Test B (TMT B) and 10-word test] and logistic regression (Clock Drawing Test). Results: In total, 199 patients completed the follow-up. The TMT B (p = 0.029) and the 10-word test (p = 0.014) were significantly associated with WMLs; however, the Clock Drawing Test (p = 0.19) was not. The TMT B (p = 0.018) and the 10-word test (p ≤ 0.001) were both significantly associated with MTLA. Conclusion: Impaired executive functioning and memory are significantly associated with WMLs and MTLA. The mechanisms explaining post-stroke cognitive impairment are multifactorial, including different types of vascular pathology and coexisting vascular and degenerative changes

    Self-reported cognitive and psychiatric symptoms at 3 months predict single-item measures of fatigue and daytime sleep 12 months after ischemic stroke

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    Introduction: Post-stroke fatigue and increased need for daytime sleep are multidimensional and insufficiently understood sequelae. Our aim was to study the relationships of self-reported cognitive and psychiatric symptoms at 3 months with fatigue and daytime sleep at 12 months post-stroke. Methods: Ischemic stroke patients without reported history of dementia or depression completed postal surveys 3- and 12-months post-stroke. At 3 months, psychiatric symptoms were assessed with the Hospital Anxiety and Depression Scale (HADS), and self-reported changes in cognitive symptoms (concentration and memory) compared to pre-stroke were assessed using single-item measures. At 12 months, single-item questions about changes in self-reported difficulties sleeping at night, fatigue and daytime sleep were included. First, we studied whether self-reported cognitive and/or psychiatric symptoms at 3 months were associated with daytime sleep and fatigue at 12 months using multiple logistic regression. Second, we fitted 2 structural equation models (SEMs) predicting fatigue and 2 models predicting daytime sleep. We compared a model where only age, sex, stroke severity (National Institutes of Health Stroke Scale; NIHSS), and difficulties sleeping at night predicted fatigue and daytime sleep at 12 months to a model where mental distress (i.e., a latent variable built of cognitive and psychiatric symptoms) was included as an additional predictor of fatigue and daytime sleep at 12 months. Results: Of 156 patients (NIHSS within 24 hours after admission (mean ± SD) = 3.6 ± 4.3, age = 73.0 ± 10.8, 41% female) 37.9% reported increased daytime sleep and 50.0% fatigue at 12 months. Increased psychiatric symptoms and worsened cognitive symptoms were associated with fatigue and daytime sleep at 12 months, after controlling for NIHSS, age, sex, and difficulties sleeping at night. SEM models including mental distress as predictor showed adequate model fit across 3 fit measures (highest RMSEA = 0.063, lowest CFI and TLI, both 0.975). Models without mental distress were not supported. Conclusion: Self-reported cognitive and psychiatric symptoms at 3 months predict increased daytime sleep and fatigue at 12 months. This highlights the relevance of monitoring cognitive and psychiatric symptoms in the subacute phase post-stroke. However, future research using validated measures of self-reported symptoms are needed to further explore these relationships.publishedVersio
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