44 research outputs found
Aberrant myocardial sheetlet mobility in hypertrophic cardiomyopathy detected using in vivo cardiovascular magnetic resonance diffusion tensor imaging
Nesting beside old nests, but not over water, increases current nest survival in a tropical mangrove-dwelling warbler
Effects of fluoxetine on functional outcomes after acute stroke (FOCUS): a pragmatic, double-blind, randomised, controlled trial
Background
Results of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects.
Methods
FOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762.
Findings
Between Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months.
Interpretation
Fluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function.
Funding
UK Stroke Association and NIHR Health Technology Assessment Programme
Age-friendly towns and cities: a mixed methods approach to developing an evaluation instrument for public health interventions
H1 Opportunity Assessment: Residential Solar Pre-cooling Opportunity Assessment: Final report November 2021
This Opportunity Assessment is a scoping study to determine what is currently understood about residential
solar pre-cooling and pre-heating (SPC/H) and therefore guide where RACE for 2030 should focus its
research efforts.
The intended outcome of SPC/H is to cost effectively shift solar energy from when it is abundant to
when energy is required for heating and cooling. The purpose is to achieve grid load smoothing
which is expected to address and peak demand and minimum demand, leading to lower customer
electricity bills, and improved solar hosting capacity.
Over the last decade significant rooftop solar photovoltaic (PV) capacity has been added in Australia, with
new installations and a growth in average system size. SPC/H is increasingly seen as an effective demand
response strategy, where the peak solar irradiance can be used to meet the peak electricity demand. It
requires market-ready remote monitoring and control technologies as well as adequate thermal inertia of
homes to reduce peak demand and therefore network infrastructure costs, consumers’ energy bills and
greenhouse gas (GHG) emissions.
Specifically, the concept of SPC and SPH requires two components:
• Reduce energy demand for home heating and cooling in the evening peak (when demand typically
peaks), and
• Soak up daytime solar power capacity (when the solar resource is typically abundant) to supply
cooling and heating.
The first focus of SPC/H is to use a household’s own PV system to power cooling and heating, but it is also
relevant for houses without PVs to soak up the excess capacity in the grid supplied by solar installations
nearby. The technologies to facilitate these two approaches are similar but the incentives for householders
will be different. Of particular concern is the ability of the building to retain the heating or cooling. Poor quality
buildings will leak the heat or coolth so that little benefit remains into the evening when needed by the
occupants. Testing this is the subject of the modelling documented in this report. The other major concern for
successful implementation of SPC/H is how well it will be accepted by consumers, what incentives may be
needed to recruit households in sufficient numbers and the possible cost and complexity of programs to
achieve the desired impact.
Smoothing out the residential load profile provides the following network benefits:
• Allows more homes to install solar because reducing peak solar export increases solar hosting
capacity, and it helps mitigate voltage rise, reducing curtailment of solar export.
• Reduces power (normal and peak) flows through transformers and cables, prolonging the life of
these assets. Peak reduction defers expensive network upgrades.
• Modulates voltage variability from solar and voltage excursion generally, making voltage
management easier
• Reduces reliance for PV inverters to engage Volt-VAr response voltage control, which in aggregate
can exchange large amounts of reactive power from the grid, increasing losses and reducing power
factor (PF).
The grid wide benefits which come from smoothing out the residential load profile include:
• Reduced load variation, increasing load forecast accuracy, and allowing for a more accurate
allocation of generation and reserves
• Less peak demand means less need for expensive peaking plants (which can sell electricity at
orders of magnitude higher price than baseload plants) and less capacity upgrades, resulting in an
overall reduction in the cost of electricit