Exploring GRIA2 Sequence Variations Using Virtual Reality

The effective visualization and presentation of biological data is of critical importance to research scientists. The increasing rate at which experiments generate data has only exacerbated the problem. While bioinformatics datasets continue to increase in size and complexity, the shift to adopt new user interface (UI) paradigms has historically lagged. Consequently, a major bottleneck for analysis of next-generation sequencing data is the continued use of UIs primarily inspired from the 1990’s through the early 2000’s. This paper presents the novel use of virtual reality (VR) as a medium for visualizing genomic, transcriptomic and proteomic data. Using the Gria2 (GluR2 or GluA2) gene and its associated gene products as our main objects of interest, we present Gria2-Viewer, a proof of concept software tool for visualizing any gene variant within the Gria2 locus. For any given genomic or transcriptomic variant of Gria2, we can quickly visualize its position on the protein subunit, rendered as a secondary structure. We also present a design for an experimental case study which compares our software versus a “traditional” workstation for ascertaining the severity of any Gria2 variant and its location within a 3d representation of the protein

Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search

Despite substantial interest in applications of neural networks to information retrieval, neural ranking models have only been applied to standard ad hoc retrieval tasks over web pages and newswire documents. This paper proposes MP-HCNN (Multi-Perspective Hierarchical Convolutional Neural Network) a novel neural ranking model specifically designed for ranking short social media posts. We identify document length, informal language, and heterogeneous relevance signals as features that distinguish documents in our domain, and present a model specifically designed with these characteristics in mind. Our model uses hierarchical convolutional layers to learn latent semantic soft-match relevance signals at the character, word, and phrase levels. A pooling-based similarity measurement layer integrates evidence from multiple types of matches between the query, the social media post, as well as URLs contained in the post. Extensive experiments using Twitter data from the TREC Microblog Tracks 2011--2014 show that our model significantly outperforms prior feature-based as well and existing neural ranking models. To our best knowledge, this paper presents the first substantial work tackling search over social media posts using neural ranking models.Comment: AAAI 2019, 10 page

A Few Good Men: A Quantitative Analysis of High-Level People\u27s Liberation Army (PLA) Promotion Patterns under Xi Jinping

China’s “striving for achievement,” or fenfa youwei (奋发有为) foreign policy strategy challenges U.S. regional primacy, emphasizes Chinese leadership in foreign affairs, and vigorously promotes economic and strategic initiatives favorable to China. According to State Department analyst Elizabeth Hague, People’s Liberation Army (PLA) promotion patterns will most likely change in response to China’s new economic and strategic demands. However, there is currently little analysis on exactly how PLA promotion patterns are changing. This thesis fills the gap by statistically analyzing how age, personal connections, education, professional experience, and foreign experience are associated with the grade promotions, not rank promotions, of 275 high-level PLA officers under Xi Jinping, defined as officers at or above the grade of corps leader (正军级). This study allows U.S. policymakers to better understand how the PLA is directing its hard power resources to support the fenfa youwei strategy, track the types of officers who are likely to fill PLA leadership positions in the future, and prepare policy responses to address shifting PLA strategic priorities. This thesis has five major findings. 1) As a high-level officer gets one year older under Xi, his or her odds of promotion decrease by a factor of .804. 2) High-level Xi-era officers who have served in the Lanzhou or Shenyang Military Regions at or above the corps leader grade sometime in their careers are more likely to receive promotions. 3) Each additional level of education (from a middle school education to a doctorate) that a high-level Xi-era officer achieves increases his or her odds of promotion by a factor of 1.413. 4) High-level Xi-era officers with experience serving in two or more PLA services, branches, and danwei (work units), at or above the corps leader grade are 2.639 times more likely to be promoted than officers without such experience. 5) Combat experience during wartime, non-combat experience (including counterterrorism experience, disaster relief experience, and experience leading military ceremonies), and international experience do not significantly increase the likelihood of high-level PLA promotions under Xi. This thesis does not address the change in the PLA’s structure that has occurred since the PLA began its massive reorganization in early 2016. New methodologies will be required to quantitatively analyze PLA promotion patterns after this reorganization