619 research outputs found

    Fresnel coefficients of a two-dimensional atomic crystal

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    In general the experiments on the linear optical properties of a single-layer two-dimensional atomic crystal are interpreted by modeling it as a homogeneous slab with an effective thickness. Here I fit the most remarkable experiments in graphene optics by using the Fresnel coefficients, fixing both the surface susceptibility and the surface conductivity of graphene. It is shown that the Fresnel coefficients and the slab model are not equivalent. Experiments indicate that the Fresnel coefficients are able to simulate the overall experiments here analyzed, while the slab model fails to predict absorption and the phase of the reflected light

    Using community interaction theory to understand the effects of group mentoring on adolescents

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    This paper describes the outcomes for adolescents taking part in a 12-week group behavioural mentoring programme and possible causal mechanisms involved, using Law's (1981) Community Interaction Theory as a theoretical framework. The two-stage qualitative research with four groups of students aged 13–14 showed that there were changes to their understanding of self, their self confidence, their ability to control emotions and behaviour and, importantly, changes in their career aspirations. Interacting with their mentors (adults from outside their previous communities) appeared to have a significant impact on them. The data suggests this was via the creation of a new community which moderated existing beliefs about who they were, and what opportunities were open to them. The mentors provided feedback, support and information, and were perceived as a credible and trusted role model. The study offers an application of Law's theory to the younger students it was developed for and provides evidence suggestive of the importance of interactions with wider communities in career development and widening participation, although future research should consider long-term follow-up of mentees

    SCiP Alliance Thriving Lives Toolkit: Implementation and Impact Evaluation

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    Primary and secondary schools responded positively to the Thriving Lives Toolkit, finding it to be a valuable resource which promoted auditing, action planning and development. All schools made progress on the principles, even when they had only been using it for a short time frame. Senior leadership support was important for facilitating this. The progress made by schools started with appointing a named contact and typically involved making use of local and national support groups and evidence based resources to increase staff awareness and implement a range of interventions. Most often these were focused on making transition more effective but schools also spent time on improving wellbeing and attainment. Schools perceived several outcomes as a consequence of this activity. School staff were more confident in supporting Service children and this had become a key activity in schools. Service children were perceived to have improved wellbeing and to be more engaged in school. Schools had improved relationships with Service families. The findings suggest that the self-assessment process enabled schools to improve their provision - engaging with the Toolkit has facilitated activity, progress and positive outcomes for Service children

    Rollup subsolar array Quarterly technical report, 5 Mar. - 30 May 1969

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    Thermal cycling and environmental tests for solar arra

    New statistical method identifes cytokines that distinguish stool microbiomes

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    Regressing an outcome or dependent variable onto a set of input or independent variables allows the analyst to measure associations between the two so that changes in the outcome can be described by and predicted by changes in the inputs. While there are many ways of doing this in classical statistics, where the dependent variable has certain properties (e.g., a scalar, survival time, count), little progress on regression where the dependent variable are microbiome taxa counts has been made that do not impose extremely strict conditions on the data. In this paper, we propose and apply a new regression model combining the Dirichlet-multinomial distribution with recursive partitioning providing a fully non-parametric regression model. This model, called DM-RPart, is applied to cytokine data and microbiome taxa count data and is applicable to any microbiome taxa count/metadata, is automatically fit, and intuitively interpretable. This is a model which can be applied to any microbiome or other compositional data and software (R package HMP) available through the R CRAN website
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