876 research outputs found

    Individualism in education reform

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    Current education reform in the U.S. is based upon a business model with capitalist market principles. High stakes standardized testing is a tool that the business model reformers use to dismantle democracy while creating an environment where a democratic society will not thrive. One of the reasons that business-minded reformers are so successful in promoting their agenda is that our society is highly individualistic. The individualistic nature of society in the U.S. provides fertile ground for reform that not only harms our present vestiges of democracy but also endangers the possibility of a democratic society for future generations. A critical analysis of individualism in U.S. culture, standardized testing, its history, and the ways in which it is used will show that individualism is a powerful cultural tradition in dominant U.S. culture. As well, the analysis will show that reformers utilizing business-model reforms and legislation desire national institutions nationally that will, to an ever-increasing extent, perpetuate a neoliberal authoritarian structure that threatens democracy

    The Gut Microbiome in Neuromyelitis Optica.

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    Neuromyelitis optica (NMO) is a rare, disabling, sometimes fatal central nervous system inflammatory demyelinating disease that is associated with antibodies ("NMO IgG") that target the water channel protein aquaporin-4 (AQP4) expressed on astrocytes. There is considerable interest in identifying environmental triggers that may elicit production of NMO IgG by AQP4-reactive B cells. Although NMO is considered principally a humoral autoimmune disease, antibodies of NMO IgG are IgG1, a T-cell-dependent immunoglobulin subclass, indicating that AQP4-reactive T cells have a pivotal role in NMO pathogenesis. When AQP4-specific proliferative T cells were first identified in patients with NMO it was discovered that T cells recognizing the dominant AQP4 T-cell epitope exhibited a T helper 17 (Th17) phenotype and displayed cross-reactivity to a homologous peptide sequence within a protein of Clostridium perfringens, a commensal bacterium found in human gut flora. The initial analysis of gut microbiota in NMO demonstrated that, in comparison to healthy controls (HC) and patients with multiple sclerosis, the microbiome of NMO is distinct. Remarkably, C. perfringens was the second most significantly enriched taxon in NMO, and among bacteria identified at the species level, C. perfringens was the one most highly associated with NMO. Those discoveries, along with evidence that certain Clostridia in the gut can regulate the balance between regulatory T cells and Th17 cells, indicate that gut microbiota, and possibly C. perfringens itself, could participate in NMO pathogenesis. Collectively, the evidence linking microbiota to humoral and cellular immunity in NMO underscores the importance for further investigating this relationship

    Design of a Constant Volume Combustion Chamber

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    This project designs a high-temperature, high-pressure fuel injection chamber for the visualization of diesel fuel injection spray patterns. The study and characterization of diesel fuel spray is important for the development of new engine designs and adoption of alternative fuels. In addition, the chamber can be used to support teaching research projects at the University of Southern Maine. A 3-D SolidWorks model is developed to meet visual accessibility and operating temperature and pressure requirements. Three experimental imaging techniques will be compared, with an emphasis on schlieren photography and videography. Data acquisition and controls systems will be developed including digital imaging through optical sensors

    Induction of Paralysis and Visual System Injury in Mice by T Cells Specific for Neuromyelitis Optica Autoantigen Aquaporin-4.

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    While it is recognized that aquaporin-4 (AQP4)-specific T cells and antibodies participate in the pathogenesis of neuromyelitis optica (NMO), a human central nervous system (CNS) autoimmune demyelinating disease, creation of an AQP4-targeted model with both clinical and histologic manifestations of CNS autoimmunity has proven challenging. Immunization of wild-type (WT) mice with AQP4 peptides elicited T cell proliferation, although those T cells could not transfer disease to naĂŻve recipient mice. Recently, two novel AQP4 T cell epitopes, peptide (p) 135-153 and p201-220, were identified when studying immune responses to AQP4 in AQP4-deficient (AQP4-/-) mice, suggesting T cell reactivity to these epitopes is normally controlled by thymic negative selection. AQP4-/- Th17 polarized T cells primed to either p135-153 or p201-220 induced paralysis in recipient WT mice, that was associated with predominantly leptomeningeal inflammation of the spinal cord and optic nerves. Inflammation surrounding optic nerves and involvement of the inner retinal layers (IRL) were manifested by changes in serial optical coherence tomography (OCT). Here, we illustrate the approaches used to create this new in vivo model of AQP4-targeted CNS autoimmunity (ATCA), which can now be employed to study mechanisms that permit development of pathogenic AQP4-specific T cells and how they may cooperate with B cells in NMO pathogenesis

    Genetic-algorithm-optimized neural networks for gravitational wave classification

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    Gravitational-wave detection strategies are based on a signal analysis technique known as matched filtering. Despite the success of matched filtering, due to its computational cost, there has been recent interest in developing deep convolutional neural networks (CNNs) for signal detection. Designing these networks remains a challenge as most procedures adopt a trial and error strategy to set the hyperparameter values. We propose a new method for hyperparameter optimization based on genetic algorithms (GAs). We compare six different GA variants and explore different choices for the GA-optimized fitness score. We show that the GA can discover high-quality architectures when the initial hyperparameter seed values are far from a good solution as well as refining already good networks. For example, when starting from the architecture proposed by George and Huerta, the network optimized over the 20-dimensional hyperparameter space has 78% fewer trainable parameters while obtaining an 11% increase in accuracy for our test problem. Using genetic algorithm optimization to refine an existing network should be especially useful if the problem context (e.g. statistical properties of the noise, signal model, etc) changes and one needs to rebuild a network. In all of our experiments, we find the GA discovers significantly less complicated networks as compared to the seed network, suggesting it can be used to prune wasteful network structures. While we have restricted our attention to CNN classifiers, our GA hyperparameter optimization strategy can be applied within other machine learning settings.Comment: 25 pages, 8 figures, and 2 tables; Version 2 includes an expanded discussion of our hyperparameter optimization mode

    UTM RTT CWG Concept & Use Cases Package #2

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    The Concept & Use Cases Package #2: Technical Capability Level 3 document represents the collaborative research efforts between the FAA and NASA as joint members of the Unmanned Aircraft System Traffic Management (UTM) Research Transition Team (RTT). Contained in this document are the 1) Terms and Definitions, 2) Foundational Principles, 3) Concept Narratives, 4) Use Cases, 5) Operational Views, and 6) Roles and Responsibilities of actors interacting within what is considered to be encompassed by Technical Capability Level 3 UTM operating environments. The contents of Package #2 should NOT be considered established policy or construed as regulatory in nature. What is presented is meant to communicate the current, agreed upon understanding between the FAA and NASA on particular features of UTM as exemplified through use cases and concept narratives for the purposes of supporting joint NASA/Industry Demonstrations and the UTM Pilot Program. It is also meant to foster discussion and refinement of the concepts and approaches being pursued by the other RTT working groups
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