Conditioned spin and charge dynamics of a single electron quantum dot

In this article we describe the incoherent and coherent spin and charge dynamics of a single electron quantum dot. We use a stochastic master equation to model the state of the system, as inferred by an observer with access to only the measurement signal. Measurements obtained during an interval of time contribute, by a past quantum state analysis, to our knowledge about the system at any time $t$ within that interval. Such analysis permits precise estimation of physical parameters, and we propose and test a modification of the classical Baum-Welch parameter re-estimation method to systems driven by both coherent and incoherent processes.Comment: 9 pages, 9 figure

Responsiveness of support systems to address refugee young people’s mental health needs: Stakeholder perspectives from Turkey and the UK

Refugee young people have high rates of unmet mental health needs. Established barriers to accessing mental health care may be contextual to the host country and its support systems. The aim of this study was to establish the perspectives of refugee young people, parents, and service providers on service responses across one middle-income and one high-income country, Turkey and the UK, respectively. In Turkey, eight professionals (social work, psychology, and education), ten parents and ten young people took part. In the UK, stakeholders included four professionals (health, educational psychology, and non-statutory), seven parents and seven young people. Data were analyzed using a codebook thematic approach. Despite structural differences between the two systems, several commonalities were identified in responses. Conceptualization of mental health, stigma, shame, and parents’ language acquisition acted as barriers to help-seeking in both countries, whilst schools were viewed as central to the initiation of interventions. Contextual barriers in Turkey included child marriage and labor, whilst reliance on non-governmental organizations (NGOs) facilitated joint care pathways. In the UK, providers aimed to adapt and extend care pathways through primary health care. Recommendations included designated policy, joint working, schools acting as service hubs, awareness, and training professionals on contextual knowledge. </p

Frailty and Social Isolation: Comparing the relationship between frailty and unidimensional and multifactorial models of social isolation.

Objective: The aim of the study was to compare uni- and multidimensional models of social isolation to improve the specificity of determining associations between social isolation and frailty. Methods: The study included participants aged ≥60 years from the English Longitudinal Study of Ageing assessed for social isolation and frailty (frailty index and Fried phenotype) over a 4-year period. Factor analysis assessed whether social isolation was multidimensional. Multiple regression analysis was used to assess specificity in associations between social isolation and frailty over time. Results: Social isolation comprises social isolation from nuclear family, other immediate family, and wider social networks. Over time, social isolation from a wider social network predicted higher frailty index levels, and higher frailty index and Fried phenotype levels predicted greater social isolation from a wider social network. Discussion: Social isolation is multidimensional. The reciprocal relationship between social isolation from wider social networks and accumulating frailty deficits, and frailty as a clinical syndrome influencing social isolation from social networks is discussed.</p

Wavelet Transformation of Genome Annotations

<div><p>(A) To illustrate the purpose of wavelet transformation, we show the original traces and continuous wavelet transformations using the derivative of Gaussian wavelet basis for gene content and divergence over a 2-Mb stretch of Chromosome 20. Colours indicate the magnitude (blue = low, red = high, white = zero) of the wavelet coefficients at each scale and location, with each level being normalised to have equal variance.</p><p>(B) Analysis of the correlation between the smoothed and detailed coefficients at each scale (see Text S2). The height of each bar is the value of the correlation coefficient and the boxes are the contributions from broader scales (top is the broadest scale), with colour intensity related to the magnitude of the effect (blue is negative, red is positive) and size proportional to the fraction of variance explained by a given level. The correlation between divergence and constraint in the original signal (−0.0823) can be decomposed into positive contributions from correlations between detail coefficients at broad scales and negative contributions from correlations between detail coefficients at fine scales.</p></div

Marginal Significance (−log₁₀ p-value as Determined by <i>t-</i>Test) of the Wavelet Coefficients from Four Annotations as Predictors of the Coefficients of the Decomposition of Human-Chimpanzee Divergence

<div><p>Red boxes highlight significant positive linear relationships, and blue boxes, negative. The intensity of the colour is proportional to the degree of significance.</p><p>(A) Smoothed coefficients.</p><p>(B) Detail coefficients.</p></div

Marginal Significance (−log₁₀ p-value as Determined by <i>t-</i>Test) of the Wavelet Coefficients from Four Annotations as Predictors of the Coefficients of the Decomposition of Ascertainment Panel Diversity

<div><p>Red boxes highlight significant positive linear relationships and blue negative. The intensity of the colour is proportional to the degree of significance.</p><p>(A) Smoothed coefficients.</p><p>(B) Detail coefficients.</p><p>Also shown is the adjusted <i>r</i>², which can be interpreted as the proportion of the variance in the signal explained by the linear model.</p></div

Quantile-Quantile Plots Showing the Difference in Allele Frequency Spectrum for AT→GC Mutations and GC→AT Mutations in Regions of Low and High Recombination

<p>If the two types of mutation were to have the same allele frequency distribution, we would expect to see a straight line. In both cases, AT→GC mutations are typically at higher frequencies than GC→AT mutations; however, the effect is more pronounced in regions of high recombination [(A), low recombination; (B), high recombination]. A quantification of the difference can be found in the text and supporting material.</p

Power Spectra and Pairwise Correlations of Detail Wavelet Coefficients

<p>Diagonal plots show the power spectrum of the wavelet decomposition of each factor on the long (red) and short (blue) arms of Chromosome 20. Off-diagonal plots show the rank correlation coefficient between pairs of detail wavelet coefficients at each scale on the long (top right) and short (bottom left) arms. Red crosses indicate significant correlations (<i>p</i>-value < 0.01; Kendall's rank correlation). Scale is shown in kilobases.</p

QQ Plot of <i>cis</i> versus <i>trans</i> HSA20 −log₁₀<i>p</i>-Values

<p>The figure shows the contrast of −log₁₀<i>p</i>-values deriving from associations of SNPs and genes within the 10-Mb region of HSA20 with −log₁₀<i>p</i>-values deriving from associations between genes on the 10-Mb region HSA20 with SNPs in one of ten ENCODE regions. Note that the distribution falls off the diagonal around −log₁₀<i>p</i> = 4, which we consider the borderline for the high enrichment of <i>cis</i> significant effects. A similar pattern is observed with any set of <i>trans</i> −log₁₀<i>p</i>-values on HSA20 or any other <i>cis</i> vs. <i>trans</i> contrast in any region we tested.</p

Continued

<p>(B) Genomic location of associated SNPs close to the <i>TMEM8</i> and <i>MRPL28</i> genes. Note the correlation between the <i>p</i>-values for the two genes. Custom tracks in the UCSC genome browser show the location of the Illumina probe and proximal SNPs in the context of genome annotation. The lower horizontal black line indicates the −log₁₀<i>p</i> threshold where the corresponding <i>q-</i>value is 0.05 (i.e., any SNPs with values −log₁₀<i>p</i> that meet or exceed this threshold are significant at the <i>q</i> = 0.05 level), and the upper line is the Bonferroni genome-wide threshold. Additional tracks describe known genes, first-exon and promoter predictions, conserved transcription factor binding sites, Gencode genes, RNA polymerase 2, and Transcription factor 2 binding sites, identified by Affymetrix ChIP/chip experiments, and Sp1 and Sp3 binding sites identified by Stanford's ChIP/chip experiments. Consensus conserved elements are shown in the final track. HapMap LD information below is for the CEU individuals (<a href="http://genome.ucsc.edu" target="_blank">http://genome.ucsc.edu</a>) [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0010078#pgen-0010078-b039" target="_blank">39</a>].</p