456 research outputs found
Goldstone Fermion Dark Matter
We propose that the fermionic superpartner of a weak-scale Goldstone boson
can be a natural WIMP candidate. The p-wave annihilation of this `Goldstone
fermion' into pairs of Goldstone bosons automatically generates the correct
relic abundance, whereas the XENON100 direct detection bounds are evaded due to
suppressed couplings to the Standard Model. Further, it is able to avoid
indirect detection constraints because the relevant s-wave annihilations are
small. The interactions of the Goldstone supermultiplet can induce non-standard
Higgs decays and novel collider phenomenology.Comment: 25 pages, 6 figures. References added, minor typos corrected.
Submitted to JHE
Focused Deterrence and the Prevention of Violent Gun Injuries: Practice, Theoretical Principles, and Scientific Evidence
Focused deterrence strategies are a relatively new addition to a growing portfolio of evidence-based violent gun injury prevention practices available to policy makers and practitioners. These strategies seek to change offender behavior by understanding the underlying violence-producing dynamics and conditions that sustain recurring violent gun injury problems and by implementing a blended strategy of law enforcement, community mobilization, and social service actions. Consistent with documented public health practice, the focused deterrence approach identifies underlying risk factors and causes of recurring violent gun injury problems, develops tailored responses to these underlying conditions, and measures the impact of implemented interventions. This article reviews the practice, theoretical principles, and evaluation evidence on focused deterrence strategies. Although more rigorous randomized studies are needed, the available empirical evidence suggests that these strategies generate noteworthy gun violence reduction impacts and should be part of a broader portfolio of violence prevention strategies available to policy makers and practitioners
SUPPORT Tools for evidence-informed health Policymaking (STP) 17: Dealing with insufficient research evidence
This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers
The distribution of pond snail communities across a landscape: separating out the influence of spatial position from local habitat quality for ponds in south-east Northumberland, UK
Ponds support a rich biodiversity because the heterogeneity of individual ponds creates, at the landscape scale, a diversity of habitats for wildlife. The distribution of pond animals and plants will be influenced by both the local conditions within a pond and the spatial distribution of ponds across the landscape. Separating out the local from the spatial is difficult because the two are often linked. Pond snails are likely to be affected by both local conditions, e.g. water hardness, and spatial patterns, e.g. distance between ponds, but studies of snail communities struggle distinguishing between the two. In this study, communities of snails were recorded from 52 ponds in a biogeographically coherent landscape in north-east England. The distribution of snail communities was compared to local environments characterised by the macrophyte communities within each pond and to the spatial pattern of ponds throughout the landscape. Mantel tests were used to partial out the local versus the landscape respective influences. Snail communities became more similar in ponds that were closer together and in ponds with similar macrophyte communities as both the local and the landscape scale were important for this group of animals. Data were collected from several types of ponds, including those created on nature reserves specifically for wildlife, old field ponds (at least 150 years old) primarily created for watering livestock and subsidence ponds outside protected areas or amongst coastal dunes. No one pond type supported all the species. Larger, deeper ponds on nature reserves had the highest numbers of species within individual ponds but shallow, temporary sites on farm land supported a distinct temporary water fauna. The conservation of pond snails in this region requires a diversity of pond types rather than one idealised type and ponds scattered throughout the area at a variety of sites, not just concentrated on nature reserves
Magnetic Fluffy Dark Matter
We explore extensions of inelastic Dark Matter and Magnetic inelastic Dark
Matter where the WIMP can scatter to a tower of heavier states. We assume a
WIMP mass GeV and a constant splitting between
successive states keV. For the
spin-independent scattering scenario we find that the direct experiments CDMS
and XENON strongly constrain most of the DAMA/LIBRA preferred parameter space,
while for WIMPs that interact with nuclei via their magnetic moment a region of
parameter space corresponding to GeV and keV
is allowed by all the present direct detection constraints.Comment: 16 pages, 6 figures, added comments about magnetic moment form factor
to Sec 3.1.2 and results to Sec 3.2.2, final version to be published in JHE
An ontological framework for cooperative games
Social intelligence is an emerging property of a system composed of agents that consists of the ability of this system to conceive, design, implement and execute strategies to solve problems and thus achieve a collective state of the system that is concurrently satisfactory for all and each one of the agents that compose it. In order to make decisions when dealing with complex problems related to social systems and take advantage of social intelligence, cooperative games theory constitutes the standard theoretical framework. In the present work, an ontological framework for cooperative games modeling and simulation is presented
A full Bayesian hierarchical mixture model for the variance of gene differential expression
<p>Abstract</p> <p>Background</p> <p>In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccurate. Visual inspection of graphical summaries of these data usually reveals that heteroscedasticity is present, and the standard approach to address this is to take a log<sub>2 </sub>transformation. In such circumstances, it is then common to assume that gene variability is constant when an analysis of these data is undertaken. However, this is perhaps too stringent an assumption. More careful inspection reveals that the simple log<sub>2 </sub>transformation does not remove the problem of heteroscedasticity. An alternative strategy is to assume independent gene-specific variances; although again this is problematic as variance estimates based on few replications are highly unstable. More meaningful and reliable comparisons of gene expression might be achieved, for different conditions or different tissue samples, where the test statistics are based on accurate estimates of gene variability; a crucial step in the identification of differentially expressed genes.</p> <p>Results</p> <p>We propose a Bayesian mixture model, which classifies genes according to similarity in their variance. The result is that genes in the same latent class share the similar variance, estimated from a larger number of replicates than purely those per gene, i.e. the total of all replicates of all genes in the same latent class. An example dataset, consisting of 9216 genes with four replicates per condition, resulted in four latent classes based on their similarity of the variance.</p> <p>Conclusion</p> <p>The mixture variance model provides a realistic and flexible estimate for the variance of gene expression data under limited replicates. We believe that in using the latent class variances, estimated from a larger number of genes in each derived latent group, the <it>p</it>-values obtained are more robust than either using a constant gene or gene-specific variance estimate.</p
Exploration of experiences in therapeutic groups for patients with severe mental illness: development of the Ferrara group experiences scale (FE-GES)
The study has been supported by the University of Ferrara (University Funds for Scientific Research 2008–2009
Towards the clinical implementation of pharmacogenetics in bipolar disorder.
BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD
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