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Stroke Survivors

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Brent Sullivan
Brent Sullivan

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A defeated character comes back after a set amount of time passes. To win the battle, all three sections of the WIN gauge at the top of the screen have to be filled; the gauge fills one section each time an opponent is defeated. Fighters can use regular attacks, power attacks, area-based attacks, and finishing moves. Regular attacks are the main part of the battle, and all combos begin with them. Power attacks leave the user open, but they have a big impact if they connect and their power can be increased by charging them up. Area-based attacks allow to hit opponents over a wide area. By using different techniques, the player can lead his team to victory; learning each character's different power, range, and effects is the first step towards being unbeatable. and the download link of this app are 100% safe.All download links of apps listed on are from Google Play Store or submitted by users.For the app from Google Play Store, won't modify it in any way.For the app submitted by users, will verify its APK signature safety before release it on our website.

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The rest of the paper is organized as follows: In Section 2 we provide an overview of Star Trek film and television series franchise. In Section 3 we introduce the LTO version 0.1.1. It is a hierarchically organized controlled vocabulary of themes, partitioned into the following four domains: the human condition, society, the pursuit of knowledge and alternate reality. There are 1535 unique themes in total. Criteria and guidelines motivating our hierarchical arrangement are discussed. In Section 4 we explain the hypergeometric testing approach to theme enrichment analysis in full technical detail. In Section 5 we use the hypergeometric test to identify enriched themes in the two Star Trek case studies outlined above. These results we compare with those obtained using the standard TF-IDF approach to enrichment analysis. We conclude the paper in Section 6 with a summary of our main contributions, a discussion of some limitations of our methodology and go on to describe a handful of possible future directions. Most notably, in terms of limitations, we emphasize that we manually annotated Star Trek episodes with themes, and as a consequence the findings we report inevitably reflect our point of view, and are not fully replicable. The theme enrichment analysis procedure based on the hypergeometric test is implemented in the R package stoRy (version 0.1.1) (Sheridan and Onsjö 2017), released through CRAN (The Comprehensive R Archive Network 2019). The thematically annotated Star Trek episode dataset is included in the package. A related R Shiny web application is available for download at the Theme Ontology GitHub repository (Theme Ontology Project GitHub Repository 2019).

The LTO follows Basic Formal Ontology (Smith and Bittner 2005) best practices (Arp et al. 2015), and is encoded using Web Ontology Language (OWL2) (Hitzler et al. 2012). LTO version 0.1.1 is available for download in OWL format at the Theme Ontology GitHub repository under a Creative Commons Attribution 4.0 International license (CC BY 4.0) (Sheridan and Onsjö 2019A). We encourage non-technical users to explore a more recent developmental version of the LTO at the Theme Ontology website (Theme Ontology 2019).

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