An Examination of Research to Practice Gaps in Education: Whole Language, Learning Modalities, and Brain Gym

The purpose of this thesis is to examine the documented research to practice gap in education by discussing three recent trends in education that gained momentum with little to no empirical support: (a) whole language reading instruction; (b) modality-based instruction; and (c) Brain Gym. This thesis examines the trend in education toward embracing unsubstantiated strategies by spotlighting these three educational trends and offers recommendations for addressing the research to practice gap in the field of education

Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.Presidential Early Career Award for Scientists and Engineers (N000141010562)United States. Army Research Office. Multidisciplinary University Research Initiative (W911NF0910541)United States. Office of Naval Research (grant N000141010841)Massachusetts Institute of Technology. Dept. of MathematicsStudienstiftung des deutschen VolkesClark BarwickJacob Luri

Explanatory pluralism in the medical sciences: theory and practice

Explanatory pluralism is the view that the best form and level of explanation depends on the kind of question one seeks to answer by the explanation, and that in order to answer all questions in the best way possible, we need more than one form and level of explanation. In the first part of this article, we argue that explanatory pluralism holds for the medical sciences, at least in theory. However, in the second part of the article we show that medical research and practice is actually not fully and truly explanatory pluralist yet. Although the literature demonstrates a slowly growing interest in non-reductive explanations in medicine, the dominant approach in medicine is still methodologically reductionist. This implies that non-reductive explanations often do not get the attention they deserve. We argue that the field of medicine could benefit greatly by reconsidering its reductive tendencies and becoming fully and truly explanatory pluralist. Nonetheless, trying to achieve the right balance in the search for and application of reductive and non-reductive explanations will in any case be a difficult exercise

The MHC class II cofactor HLA-DM interacts with Ig in B cells

International audienceB cells internalize extracellular Ag into endosomes using the Ig component of the BCR. In endosomes, Ag-derived peptides are loaded onto MHC class II proteins. How these pathways intersect remains unclear. We find that HLA-DM (DM), a catalyst for MHC class II peptide loading, coprecipitates with Ig in lysates from human tonsillar B cells and B cell lines. The molecules in the Ig/DM complexes have mature glycans, and the complexes colocalize with endosomal markers in intact cells. A larger fraction of Ig precipitates with DM after BCR crosslinking, implying that complexes can form when DM meets endocytosed Ig. In vitro, in the endosomal pH range, soluble DM directly binds the Ig Fab domain and increases levels of free Ag released from immune complexes. Taken together, these results argue that DM and Ig intersect in the endocytic pathway of B cells with potential functional consequences

FPGA-based tracking for the CMS Level-1 trigger using the tracklet algorithm

The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charged particle trajectories and their inclusion in the hardware-based trigger system. There are many challenges involved in achieving this: a large input data rate of about 20--40\,Tb/s; processing a new batch of input data every 25\,ns, each consisting of about 15,000 precise position measurements and rough transverse momentum measurements of particles (``stubs''); performing the pattern recognition on these stubs to find the trajectories; and producing the list of trajectory parameters within $4\,\mu$s. This paper describes a proposed solution to this problem, specifically, it presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The results of an end-to-end demonstrator system, based on Xilinx Virtex-7 FPGAs, that meets timing and performance requirements are presented along with a further improved, optimized version of the algorithm together with its corresponding expected performance