248 research outputs found
Carers Create: carer perspectives of a creative programme for people with dementia and their carers on the relationship within the (carer and cared for) dyad
Introduction
Relationships between people with dementia and their carers can prove challenging over the trajectory of the disease. Interventions with a potential to address this include arts and music-based activities. This research project aimed to evaluate a community engagement programme (Carers Create) where both people with dementia and their carers participate together in singing and other activities. A specific focus was on the impact of the sessions on the dyadic relationship.
Methods
A grounded theory approach involved conducting three focus group interviews with carers of people with dementia (n=16) facilitated by members of a local U3A (University of the Third Age) who were trained and supported by university researchers. Recorded conversations were transcribed and analysed using a three-stage coding and thematic development technique.
Results
Four overarching themes were identified from the discourse: remembering the positive qualities of the cared-for; the physical and emotional demands of caring; Carers Create as a shared, beneficial activity; the enduring value of Carers Create.
Conclusion
Carers found the sessions to positively influence the relationship with the person they cared for through offering some relief from the day-to-day pressures of caring and in some cases restoring elements of a previously strong relationship. Crucial to the experience was the fact that the sessions included both carer and cared-for, offering activities to do together, and that they took place within a group, thereby offering a degree of mutual support. In addition, some carers were able to build on learning which had taken place and use certain techniques, such as singing, to help manage care, thus extending the improved relationship.
Regularizing Portfolio Optimization
The optimization of large portfolios displays an inherent instability to
estimation error. This poses a fundamental problem, because solutions that are
not stable under sample fluctuations may look optimal for a given sample, but
are, in effect, very far from optimal with respect to the average risk. In this
paper, we approach the problem from the point of view of statistical learning
theory. The occurrence of the instability is intimately related to over-fitting
which can be avoided using known regularization methods. We show how
regularized portfolio optimization with the expected shortfall as a risk
measure is related to support vector regression. The budget constraint dictates
a modification. We present the resulting optimization problem and discuss the
solution. The L2 norm of the weight vector is used as a regularizer, which
corresponds to a diversification "pressure". This means that diversification,
besides counteracting downward fluctuations in some assets by upward
fluctuations in others, is also crucial because it improves the stability of
the solution. The approach we provide here allows for the simultaneous
treatment of optimization and diversification in one framework that enables the
investor to trade-off between the two, depending on the size of the available
data set
Establishing Lagrangian connections between observations within air masses crossing the Atlantic during the International Consortium for Atmospheric Research on Transport and Transformation experiment
The ITCT-Lagrangian-2K4 (Intercontinental Transport and Chemical Transformation) experiment was conceived with an aim to quantify the effects of photochemistry and mixing on the transformation of air masses in the free troposphere away from emissions. To this end, attempts were made to intercept and sample air masses several times during their journey across the North Atlantic using four aircraft based in New Hampshire (USA), Faial (Azores) and Creil (France). This article begins by describing forecasts from two Lagrangian models that were used to direct the aircraft into target air masses. A novel technique then identifies Lagrangian matches between flight segments. Two independent searches are conducted: for Lagrangian model matches and for pairs of whole air samples with matching hydrocarbon fingerprints. The information is filtered further by searching for matching hydrocarbon samples that are linked by matching trajectories. The quality of these "coincident matches'' is assessed using temperature, humidity and tracer observations. The technique pulls out five clear Lagrangian cases covering a variety of situations and these are examined in detail. The matching trajectories and hydrocarbon fingerprints are shown, and the downwind minus upwind differences in tracers are discussed
Discovery of the rpl10 Gene in Diverse Plant Mitochondrial Genomes and Its Probable Replacement by the Nuclear Gene for Chloroplast RPL10 in Two Lineages of Angiosperms
Mitochondrial genomes of plants are much larger than those of mammals and often contain conserved open reading frames (ORFs) of unknown function. Here, we show that one of these conserved ORFs is actually the gene for ribosomal protein L10 (rpl10) in plant. No rpl10 gene has heretofore been reported in any mitochondrial genome other than the exceptionally gene-rich genome of the protist Reclinomonas americana. Conserved ORFs corresponding to rpl10 are present in a wide diversity of land plant and green algal mitochondrial genomes. The mitochondrial rpl10 genes are transcribed in all nine land plants examined, with five seed plant genes subject to RNA editing. In addition, mitochondrial-rpl10-like cDNAs were identified in EST libraries from numerous land plants. In three lineages of angiosperms, rpl10 is either lost from the mitochondrial genome or a pseudogene. In two of them (Brassicaceae and monocots), no nuclear copy of mitochondrial rpl10 is identifiably present, and instead a second copy of nuclear-encoded chloroplast rpl10 is present. Transient assays using green fluorescent protein indicate that this duplicate gene is dual targeted to mitochondria and chloroplasts. We infer that mitochondrial rpl10 has been functionally replaced by duplicated chloroplast counterparts in Brassicaceae and monocots
Local Analysis of Dissipative Dynamical Systems
Linear transformation techniques such as singular value decomposition (SVD)
have been used widely to gain insight into the qualitative dynamics of data
generated by dynamical systems. There have been several reports in the past
that had pointed out the susceptibility of linear transformation approaches in
the presence of nonlinear correlations. In this tutorial review, local
dispersion along with the surrogate testing is proposed to discriminate
nonlinear correlations arising in deterministic and non-deterministic settings.Comment: 85 Pages, 13 Figure
Making sense of perceptions of risk of diseases and vaccinations: a qualitative study combining models of health beliefs, decision-making and risk perception
<p>Abstract</p> <p>Background</p> <p>Maintaining high levels of childhood vaccinations is important for public health. Success requires better understanding of parents' perceptions of diseases and consequent decisions about vaccinations, however few studies have considered this from the theoretical perspectives of risk perception and decision-making under uncertainty. The aim of this study was to examine the utility of subjective risk perception and decision-making theories to provide a better understanding of the differences between immunisers' and non-immunisers' health beliefs and behaviours.</p> <p>Methods</p> <p>In a qualitative study we conducted semi-structured in-depth interviews with 45 Australian parents exploring their experiences and perceptions of disease severity and susceptibility. Using scenarios about 'a new strain of flu' we explored how risk information was interpreted.</p> <p>Results</p> <p>We found that concepts of dread, unfamiliarity, and uncontrollability from the subjective perception of risk and ambiguity, optimistic control and omission bias from explanatory theories of decision-making under uncertainty were useful in understanding why immunisers, incomplete immunisers and non-immunisers interpreted severity and susceptibility to diseases and vaccine risk differently. Immunisers dreaded unfamiliar diseases whilst non-immunisers dreaded unknown, long term side effects of vaccines. Participants believed that the risks of diseases and complications from diseases are not equally spread throughout the community, therefore, when listening to reports of epidemics, it is not the number of people who are affected but the familiarity or unfamiliarity of the disease and the characteristics of those who have had the disease that prompts them to take preventive action. Almost all believed they themselves would not be at serious risk of the 'new strain of flu' but were less willing to take risks with their children's health.</p> <p>Conclusion</p> <p>This study has found that health messages about the risks of disease which are communicated as though there is equality of risk in the population may be unproductive as these messages are perceived as unbelievable or irrelevant. The findings from this study have implications beyond the issue of childhood vaccinations as we grapple with communicating risks of new epidemics, and indeed may usefully contribute to the current debate especially in the UK of how these theories of risk and decision-making can be used to 'nudge' other health behaviours.</p
Phase I and pharmacokinetic study of XR11576, an oral topoisomerase I and II inhibitor, administered on days 1–5 of a 3-weekly cycle in patients with advanced solid tumours
XR11576 is an oral topoisomerase I and II inhibitor. The objectives of this phase I study were to assess the dose-limiting toxicities (DLTs), to determine the maximum tolerated dose (MTD) and to describe the pharmacokinetics (PKs) of XR11576 when administered orally on days 1-5 every 3 weeks to patients with advanced solid tumours. Patients were treated with escalating doses of XR11576 at doses ranging from 30
Linear Predictability vs. Bull and Bear Market Models in Strategic Asset Allocation Decisions: Evidence from UK Data
Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets through careful selection of predictor variables that capture business cycles and market sentiment. Yet, a distinct literature exists that shows that nonlinear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. This paper examines whether and how simple VARs can produce portfolio rules similar to those obtained under a simple Markov switching, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem for U.K. data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those of nonlinear models. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (net of transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks
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