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  1. added 2016-06-22
    Guram Bezhanishvili & Wesley H. Holliday (forthcoming). Locales, Nuclei, and Dragalin Frames. In Lev Beklemishev & Stéphane Demri (eds.), Advances in Modal Logic, Vol. 11. College Publications
    It is a classic result in lattice theory that a poset is a complete lattice iff it can be realized as fixpoints of a closure operator on a powerset. Dragalin [9,10] observed that a poset is a locale (complete Heyting algebra) iff it can be realized as fixpoints of a nucleus on the locale of upsets of a poset. He also showed how to generate a nucleus on upsets by adding a structure of “paths” to a poset, forming what we (...)
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  2. added 2016-06-22
    Anita Bandrowski, Ryan Brinkman, Mathias Brochhausen, Matthew H. Brush, Bill Bug, Marcus C. Chibucos, Kevin Clancy, Mélanie Courtot, Dirk Derom, Michel Dumontier, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Frank Gibson, Alejandra Gonzalez-Beltran, Melissa A. Haendel, Yongqun He, Mervi Heiskanen, Tina Hernandez-Boussard, Mark Jensen, Yu Lin, Allyson L. Lister, Phillip Lord, James Malone, Elisabetta Manduchi, Monnie McGee, Norman Morrison, James A. Overton, Helen Parkinson, Bjoern Peters, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Daniel Schober, Barry Smith, Larisa N. Soldatova, Christian J. Stoeckert, Chris F. Taylor, Carlo Torniai, Jessica A. Turner, Randi Vita, Patricia L. Whetzel & Jie Zheng (2016). The Ontology for Biomedical Investigations. PLoS ONE 11 (4):e0154556.
    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...)
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  3. added 2016-06-09
    Ingo Brigandt, Sara Green & Maureen A. O'Malley (forthcoming). Systems Biology and Mechanistic Explanation. In Stuart Glennan & Phyllis Illari (eds.), The Routledge Handbook of Mechanisms and Mechanical Philosophy.
  4. added 2016-05-19
    Valérie Lynn Therrien (2012). INVENTING LOGIC: THE LÖWENHEIM-SKOLEM THEOREM AND FIRST- AND SECOND-ORDER LOGIC. Pensées Canadiennes 10.
  5. added 2016-05-16
    Hisham Khdair (2015). SP2MN: A Software Process Meta-Modeling Language. International Review on Computers and Software 10 (7):726-734.
    In the last two decades, software process modeling has been an area of interest within both academia and industry. Software process modeling aims at defining and representing software processes in the form of models. A software process model represents the medium that allows better understanding, management and control of the software process. Software process metamodeling rather, provides standard metamodels which enable the defining of customized software process models for a specific project in hand by instantiation. Several software process modeling/meta-modeling languages (...)
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  6. added 2016-04-26
    Fionn Murtagh & Giuseppe Iurato, Jacques Lacan’s Registers of the Psychoanalytic Field, Applied Using Geometric Data Analysis to Edgar Allan Poe’s “The Purloined Letter”.
    In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more Comprehensive investigation, we develop an approach for revealing, that is, uncovering, Lacanian (...)
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  7. added 2016-04-03
    Jianfu Chen (2015). Language Grounding in Massive Online Data. The Classical Review 1.
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  8. added 2016-04-02
    Xiaocheng Tang (2015). Big Data Optimization in Machine Learning. Disertation 1.
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