University of Memphis

About: University of Memphis is a education organization based out in Memphis, Tennessee, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 7710 authors who have published 20082 publications receiving 611618 citations. The organization is also known as: U of M.

Representation and American Governing Institutions

Abstract: We isolate two limitations of the existing literature on representation and then move toward some important remedies. The first limitation is that typical representation studies assess the extent to which policymakers’ issue positions correspond to those of the public, but do not investigate whether the issue priorities of policymakers correspond to those of the public. The second limitation is that existing studies do not consider the full policymaking process, from agenda setting to enactment. Using data provided by the Policy Agendas and Congressional Bills Projects, we investigate how well the public's policy priorities have been represented in national policymaking over a 47-year time period. We first assess public concern about 18 major issues using Most Important Problem data (1956–2002) and then correlate these concerns with changing issue attention across 10 policymaking channels that are ordered by differences in institutional friction. We find much closer correspondence where friction i...

Enactive Metaphors: Learning Through Full-Body Engagement

Abstract: Building on both cognitive semantics and enactivist approaches to cognition, we explore the concept of enactive metaphor and its implications for learning. Enactive approaches to cognition involve the idea that online sensory-motor and affective processes shape the way the perceiver-thinker experiences the world and interacts with others. Specifically, we argue for an approach to learning through whole-body engagement in a way that employs enactive metaphors. We summarize recent empirical studies that show enactive metaphors and whole-body involvement in virtual and mixed reality environments support and improve learning.

A Selective Review of Multi-Level Omics Data Integration Using Variable Selection.

Abstract: High-throughput technologies have been used to generate a large amount of omics data. In the past, single-level analysis has been extensively conducted where the omics measurements at different levels, including mRNA, microRNA, CNV and DNA methylation, are analyzed separately. As the molecular complexity of disease etiology exists at all different levels, integrative analysis offers an effective way to borrow strength across multi-level omics data and can be more powerful than single level analysis. In this article, we focus on reviewing existing multi-omics integration studies by paying special attention to variable selection methods. We first summarize published reviews on integrating multi-level omics data. Next, after a brief overview on variable selection methods, we review existing supervised, semi-supervised and unsupervised integrative analyses within parallel and hierarchical integration studies, respectively. The strength and limitations of the methods are discussed in detail. No existing integration method can dominate the rest. The computation aspects are also investigated. The review concludes with possible limitations and future directions for multi-level omics data integration.