98 research outputs found

    Applying Emotional Analysis for Automated Content Moderation

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    The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing a system to configure tolerance thresholds on a per-emotion basis, implementing the process of determining violations of incoming text posts using the configuration, and testing the effectiveness of the emotional analysis algorithm at determining toxic posts using a dataset of posts that have been manually reviewed for toxicity by a group of human moderators

    Resonance Raman spectroscopy of manganese(III) etioporphyrin I : theory and experiment

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    Ph.D.Donald C. O'She

    Relative contributions of scattering equation terms to the resonance spectra of synthetic metalloporphyrins

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    Issued as Yearly technical letter report, and Final project report, Project no. G-41-66

    Tetracycloalkenyl-meso-tetraphenylporphyrins as Models for the Effect of Non-planarity on the Light Absorption Properties of Photosynthetic Chromophores

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    As the size of the cycloalkenyl ring in synthetic C5-C7 tetracycloalkenyl-meso-tetraphenylporphyrins (TCnTPP) is increased the porphyrin core changes from planar to non-planar, showing that porphyrins with well-defined degrees of ruffling can be synthesized for use in systematic studies to determine the effects of non-planarity

    Improving electronic structure methods to predict nano-optoelectronics and nano-catalyst functions.

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    This report focuses on quantum chemistry and ab initio molecular dynamics (AIMD) calculations applied to elucidate the mechanism of the multi-step, 2-electron, electrochemical reduction of the green house gas molecule carbon dioxide (CO{sub 2}) to carbon monoxide (CO) in aqueous media. When combined with H{sub 2} gas to form synthesis ('syn') gas, CO becomes a key precursor to methane, methanol, and other useful hydrocarbon products. To elucidate the mechanism of this reaction, we apply computational electrochemistry which is a fledgling, important area of basic science critical to energy storage. This report highlights several approaches, including the calculation of redox potentials, the explicit depiction of liquid water environments using AIMD, and free energy methods. While costly, these pioneering calculations reveal the key role of hydration- and protonation-stabilization of reaction intermediates, and may inform the design of CO{sub 2}-capture materials as well as its electrochemical reduction. In the course of this work, we have also dealt with the challenges of identifying and applying electronic structure methods which are sufficiently accurate to deal with transition metal ion complex-based catalyst. Such electronic structure methods are also pertinent to the accurate modeling of actinide materials and therefore to nuclear energy research. Our multi-pronged effort towards achieving this titular goal of the LDRD is discussed
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