1,087 research outputs found
Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus
BACKGROUND: Diabetes is one of the commonest chronic medical conditions, affecting around 347 million adults worldwide. Structured patient education programmes reduce the risk of diabetes-related complications four-fold. Internet-based self-management programmes have been shown to be effective for a number of long-term conditions, but it is unclear what are the essential or effective components of such programmes. If computer-based self-management interventions improve outcomes in type 2 diabetes, they could potentially provide a cost-effective option for reducing the burdens placed on patients and healthcare systems by this long-term condition. OBJECTIVES: To assess the effects on health status and health-related quality of life of computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. SEARCH METHODS: We searched six electronic bibliographic databases for published articles and conference proceedings and three online databases for theses (all up to November 2011). Reference lists of relevant reports and reviews were also screened. SELECTION CRITERIA: Randomised controlled trials of computer-based self-management interventions for adults with type 2 diabetes, i.e. computer-based software applications that respond to user input and aim to generate tailored content to improve one or more self-management domains through feedback, tailored advice, reinforcement and rewards, patient decision support, goal setting or reminders. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the abstracts and extracted data. A taxonomy for behaviour change techniques was used to describe the active ingredients of the intervention. MAIN RESULTS: We identified 16 randomised controlled trials with 3578 participants that fitted our inclusion criteria. These studies included a wide spectrum of interventions covering clinic-based brief interventions, Internet-based interventions that could be used from home and mobile phone-based interventions. The mean age of participants was between 46 to 67 years old and mean time since diagnosis was 6 to 13 years. The duration of the interventions varied between 1 to 12 months. There were three reported deaths out of 3578 participants.Computer-based diabetes self-management interventions currently have limited effectiveness. They appear to have small benefits on glycaemic control (pooled effect on glycosylated haemoglobin A1c (HbA1c): -2.3 mmol/mol or -0.2% (95% confidence interval (CI) -0.4 to -0.1; P = 0.009; 2637 participants; 11 trials). The effect size on HbA1c was larger in the mobile phone subgroup (subgroup analysis: mean difference in HbA1c -5.5 mmol/mol or -0.5% (95% CI -0.7 to -0.3); P < 0.00001; 280 participants; three trials). Current interventions do not show adequate evidence for improving depression, health-related quality of life or weight. Four (out of 10) interventions showed beneficial effects on lipid profile.One participant withdrew because of anxiety but there were no other documented adverse effects. Two studies provided limited cost-effectiveness data - with one study suggesting costs per patient of less than $140 (in 1997) or 105 EURO and another study showed no change in health behaviour and resource utilisation. AUTHORS' CONCLUSIONS: Computer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control and the effect was larger in the mobile phone subgroup. There is no evidence to show benefits in other biological outcomes or any cognitive, behavioural or emotional outcomes
Joining the conspiracy? Negotiating ethics and emotions in researching (around) AIDS in southern Africa
AIDS is an emotive subject, particularly in southern Africa. Among those who have been directly affected by the disease, or who perceive themselves to be personally at risk, talking about AIDS inevitably arouses strong emotions - amongst them fear, distress, loss and anger. Conventionally, human geography research has avoided engagement with such emotions. Although the ideal of the detached observer has been roundly critiqued, the emphasis in methodological literature on 'doing no harm' has led even qualitative researchers to avoid difficult emotional encounters. Nonetheless, research is inevitably shaped by emotions, not least those of the researchers themselves. In this paper, we examine the role of emotions in the research process through our experiences of researching the lives of 'Young AIDS migrants' in Malawi and Lesotho. We explore how the context of the research gave rise to the production of particular emotions, and how, in response, we shaped the research, presenting a research agenda focused more on migration than AIDS. This example reveals a tension between universalised ethics expressed through ethical research guidelines that demand informed consent, and ethics of care, sensitive to emotional context. It also demonstrates how dualistic distinctions between reason and emotion, justice and care, global and local are unhelpful in interpreting the ethics of research practice
Strategies used as spectroscopy of financial markets reveal new stylized facts
We propose a new set of stylized facts quantifying the structure of financial
markets. The key idea is to study the combined structure of both investment
strategies and prices in order to open a qualitatively new level of
understanding of financial and economic markets. We study the detailed order
flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This
enormous dataset allows us to compare (i) a closed national market (A-shares)
with an international market (B-shares), (ii) individuals and institutions and
(iii) real investors to random strategies with respect to timing that share
otherwise all other characteristics. We find that more trading results in
smaller net return due to trading frictions. We unveiled quantitative power
laws with non-trivial exponents, that quantify the deterioration of performance
with frequency and with holding period of the strategies used by investors.
Random strategies are found to perform much better than real ones, both for
winners and losers. Surprising large arbitrage opportunities exist, especially
when using zero-intelligence strategies. This is a diagnostic of possible
inefficiencies of these financial markets.Comment: 13 pages including 5 figures and 1 tabl
Increased entropy of signal transduction in the cancer metastasis phenotype
Studies into the statistical properties of biological networks have led to
important biological insights, such as the presence of hubs and hierarchical
modularity. There is also a growing interest in studying the statistical
properties of networks in the context of cancer genomics. However, relatively
little is known as to what network features differ between the cancer and
normal cell physiologies, or between different cancer cell phenotypes. Based on
the observation that frequent genomic alterations underlie a more aggressive
cancer phenotype, we asked if such an effect could be detectable as an increase
in the randomness of local gene expression patterns. Using a breast cancer gene
expression data set and a model network of protein interactions we derive
constrained weighted networks defined by a stochastic information flux matrix
reflecting expression correlations between interacting proteins. Based on this
stochastic matrix we propose and compute an entropy measure that quantifies the
degree of randomness in the local pattern of information flux around single
genes. By comparing the local entropies in the non-metastatic versus metastatic
breast cancer networks, we here show that breast cancers that metastasize are
characterised by a small yet significant increase in the degree of randomness
of local expression patterns. We validate this result in three additional
breast cancer expression data sets and demonstrate that local entropy better
characterises the metastatic phenotype than other non-entropy based measures.
We show that increases in entropy can be used to identify genes and signalling
pathways implicated in breast cancer metastasis. Further exploration of such
integrated cancer expression and protein interaction networks will therefore be
a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table
Energy modellers should explore extremes more systematically in scenarios
Scenarios are the primary tool for examining how current decisions shape the future, but the future is affected as much by out-of-ordinary extremes as by generally expected trends. Energy modellers can study extremes both by incorporating them directly within models and by using complementary off-model analyses
Manipulating infrared photons using plasmons in transparent graphene superlattices
Superlattices are artificial periodic nanostructures which can control the
flow of electrons. Their operation typically relies on the periodic modulation
of the electric potential in the direction of electron wave propagation. Here
we demonstrate transparent graphene superlattices which can manipulate infrared
photons utilizing the collective oscillations of carriers, i.e., plasmons of
the ensemble of multiple graphene layers. The superlattice is formed by
depositing alternating wafer-scale graphene sheets and thin insulating layers,
followed by patterning them all together into 3-dimensional
photonic-crystal-like structures. We demonstrate experimentally that the
collective oscillation of Dirac fermions in such graphene superlattices is
unambiguously nonclassical: compared to doping single layer graphene,
distributing carriers into multiple graphene layers strongly enhances the
plasmonic resonance frequency and magnitude, which is fundamentally different
from that in a conventional semiconductor superlattice. This property allows us
to construct widely tunable far-infrared notch filters with 8.2 dB rejection
ratio and terahertz linear polarizers with 9.5 dB extinction ratio, using a
superlattice with merely five graphene atomic layers. Moreover, an unpatterned
superlattice shields up to 97.5% of the electromagnetic radiations below 1.2
terahertz. This demonstration also opens an avenue for the realization of other
transparent mid- and far-infrared photonic devices such as detectors,
modulators, and 3-dimensional meta-material systems.Comment: under revie
Reservoir Topology in Deep Echo State Networks
Deep Echo State Networks (DeepESNs) recently extended the applicability of
Reservoir Computing (RC) methods towards the field of deep learning. In this
paper we study the impact of constrained reservoir topologies in the
architectural design of deep reservoirs, through numerical experiments on
several RC benchmarks. The major outcome of our investigation is to show the
remarkable effect, in terms of predictive performance gain, achieved by the
synergy between a deep reservoir construction and a structured organization of
the recurrent units in each layer. Our results also indicate that a
particularly advantageous architectural setting is obtained in correspondence
of DeepESNs where reservoir units are structured according to a permutation
recurrent matrix.Comment: Preprint of the paper published in the proceedings of ICANN 201
A fractal dimension for measures via persistent homology
We use persistent homology in order to define a family of fractal dimensions,
denoted for each homological dimension
, assigned to a probability measure on a metric space. The case
of -dimensional homology () relates to work by Michael J Steele (1988)
studying the total length of a minimal spanning tree on a random sampling of
points. Indeed, if is supported on a compact subset of Euclidean space
for , then Steele's work implies that
if the absolutely continuous part of
has positive mass, and otherwise .
Experiments suggest that similar results may be true for higher-dimensional
homology , though this is an open question. Our fractal dimension is
defined by considering a limit, as the number of points goes to infinity,
of the total sum of the -dimensional persistent homology interval lengths
for random points selected from in an i.i.d. fashion. To some
measures we are able to assign a finer invariant, a curve measuring the
limiting distribution of persistent homology interval lengths as the number of
points goes to infinity. We prove this limiting curve exists in the case of
-dimensional homology when is the uniform distribution over the unit
interval, and conjecture that it exists when is the rescaled probability
measure for a compact set in Euclidean space with positive Lebesgue measure
- …