5 research outputs found

    Hierarchical Structure of Magnetohydrodynamic Turbulence In Position-Position-Velocity Space

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    Magnetohydrodynamic turbulence is able to create hierarchical structures in the interstellar medium that are correlated on a wide range of scales via the energy cascade. We use hierarchical tree diagrams known as dendrograms to characterize structures in synthetic Position-Position-Velocity (PPV) emission cubes of optically thin isothermal magnetohydrodynamic turbulence. We show that the structures and degree of hierarchy observed in PPV space are related to the physics of the gas, i.e. self-gravity and the global sonic and Alfvenic Mach number. Simulations with higher Alfvenic Mach number, self-gravity and supersonic flows display enhanced hierarchical structure. We observed a strong sonic and Alfvenic dependency when we apply the the statistical moments (i.e. mean, variance, skewness, kurtosis) to the dendrogram distribution. Larger magnetic field and sonic Mach number correspond to larger values of the moments. Application of the dendrogram to 3D density cubes, also known as Position-Position-Position cubes (PPP), reveals that the dominant emission contours in PPP and PPV are related for supersonic gas but not for subsonic. We also explore the effects of smoothing, thermal broadening and velocity resolution on the dendrograms in order to make our study more applicable to observational data. These results all point to hierarchical tree diagrams as being a promising additional tool for studying ISM turbulence and star forming regions in the direction of obtaining information on the degree of self-gravity, the Mach numbers and the complicated relationship between PPV and PPP.Comment: submitted to Ap

    A systematic review of randomized trials for engaging socially disadvantaged groups in health research: A distillation approach

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    A systematic distallation of randomized community engagement interventions targeted at increasing research participation in social disadvantaged group

    A systematic review of randomized trials for engaging socially disadvantaged groups in health research: A distillation approach

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    Research that fails to include sufficient representation from socially disadvantaged groups cannot make strong inferences about those groups. This relative lack of knowledge poses theoretical and clinical problems for health research. More effective community engagement with socially disadvantaged groups is often proposed as a way to increase research engagement. However, community engagement is a heterogeneous construct, including everything from how participants are contacted to whether researchers work with an organization within the community. Further, community engagement efforts vary widely in their effectiveness in recruiting and retaining participants from socially disadvantaged groups. Therefore, some types of community engagement may be more effective than others. We conducted a systematic review of randomized controlled trials attempting to increase recruitment or retention of socially disadvantaged groups. We then applied systematic distillation procedures to examine which components of community engagement interventions were associated with successful recruitment or retention outcomes. Generally, we found research process related variables (e.g. having a systematic contact plan) most frequently differentiated effective vs. ineffective recruitment or retention outcomes. Partial associations between components in effective interventions, including negative associations, were descriptively stronger than partial associations in the ineffective interventions, indicating targeted interventions may be more effective than more generalized interventions. The literature was also relatively sparse and at unclear-to-high-risk for bias. Future pre-registered, research process-oriented, and targeted recruitment and retention interventions may increase the research participation of socially disadvantaged groups in health research
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