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The docket sheet of a court case contains a wealth of information about the progression of a case, the parties’ and judge’s decision-making along the way, and the case’s ultimate outcome that can be used in analytical applications. However, the unstructured text of the docket sheet and the terse and variable phrasing of docket entries require the development of new models to identify key entities to enable analysis at a systematic level. We developed a judge entity recognition language model and disambiguation pipeline for US District Court records. Our model can robustly identify mentions of judicial entities in free text (~99% F-1 Score) and outperforms general state-of-the-art language models by 13%. Our disambiguation pipeline is able to robustly identify both appointed and non-appointed judicial actors and correctly infer the type of appointment (~99% precision). Lastly, we show with a case study on in forma pauperis decision-making that there is substantial error (~30%) attributing decision outcomes to judicial actors if the free text of the docket is not used to make the identification and attribution. 

The U.S. court system is the nation's arbiter of justice, tasked with the responsibility of ensuring equal protection under the law. But hurdles to information access obscure the inner workings of the system, preventing stakeholders - from legal scholars to journalists and members of the public - from understanding the state of justice in America at scale. There is an ongoing data access argument here: U.S. court records are public data and should be freely available. But open data arguments represent a half-measure; what we really need is open information. This distinction marks the difference between downloading a zip file containing a quarter-million case dockets and getting the real-time answer to a question like "Are pro se parties more or less likely to receive fee waivers?" To help bridge that gap, we introduce a novel platform and user experience that provides users with the tools necessary to explore data and drive analysis via natural language statements. Our approach leverages an ontology configuration that adds domain-relevant data semantics to database schemas to provide support for user guidance and for search and analysis without user-entered code or SQL. The system is embodied in a "natural-language notebook" user experience, and we apply this approach to the space of case docket data from the U.S. federal court system. Additionally, we provide detail on the collection, ingestion and processing of the dockets themselves, including early experiments in the use of language modeling for docket entry classification with an initial focus on motions. 

The airway epithelium serves as the interface between the host and external environment. In many chronic lung diseases, the airway is the site of substantial remodeling after injury. While, idiopathic pulmonary fibrosis (IPF) has traditionally been considered a disease of the alveolus and lung matrix, the dominant environmental (cigarette smoking) and genetic (gain of functionMUC5Bpromoter variant) risk factor primarily affect the distal airway epithelium. Moreover, airway-specific pathogenic features of IPF include bronchiolization of the distal airspace with abnormal airway cell-types and honeycomb cystic terminal airway-like structures with concurrent loss of terminal bronchioles in regions of minimal fibrosis. However, the pathogenic role of the airway epithelium in IPF is unknown. Combining biophysical, genetic, and signaling analyses of primary airway epithelial cells, we demonstrate that healthy and IPF airway epithelia are biophysically distinct, identifying pathologic activation of the ERBB-YAP axis as a specific and modifiable driver of prolongation of the unjammed-to-jammed transition in IPF epithelia. Furthermore, we demonstrate that this biophysical state and signaling axis correlates with epithelial-driven activation of the underlying mesenchyme. Our data illustrate the active mechanisms regulating airway epithelial-driven fibrosis and identify targets to modulate disease progression.

 

The need for improvement of societal disaster resilience and response efforts was evident after the destruction caused by the 2017 Atlantic hurricane season. We present a novel conceptual framework for improving disaster resilience through the combination of serious games, geographic information systems (GIS), spatial thinking, and disaster resilience. Our framework is implemented via Project Lily Pad, a serious geogame based on our conceptual framework, serious game case studies, interviews and real-life experiences from 2017 Hurricane Harvey survivors in Dickinson, TX, and an immersive hurricane-induced flooding scenario. The game teaches a four-fold set of skills relevant to spatial thinking and disaster resilience, including reading a map, navigating an environment, coding verbal instructions, and determining best practices in a disaster situation. Results of evaluation of the four skills via Project Lily Pad through a “think aloud” study conducted by both emergency management novices and professionals revealed that the game encouraged players to think spatially, can help build awareness for disaster response scenarios, and has potential for real-life use by emergency management professionals. It can be concluded from our results that the combination of serious games, geographic information systems (GIS), spatial thinking, and disaster resilience, as implemented via Project Lily Pad and our evaluation results, demonstrated the wide range of possibilities for using serious geogames to improve disaster resilience spatial thinking and potentially save lives when disasters occur. 

Abstract Fusarium oxysporum is a cross-kingdom fungal pathogen that infects plants and humans. Horizontally transferred lineage-specific (LS) chromosomes were reported to determine host-specific pathogenicity among phytopathogenic F. oxysporum . However, the existence and functional importance of LS chromosomes among human pathogenic isolates are unknown. Here we report four unique LS chromosomes in a human pathogenic strain NRRL 32931, isolated from a leukemia patient. These LS chromosomes were devoid of housekeeping genes, but were significantly enriched in genes encoding metal ion transporters and cation transporters. Homologs of NRRL 32931 LS genes, including a homolog of ceruloplasmin and the genes that contribute to the expansion of the alkaline pH-responsive transcription factor PacC/Rim1p, were also present in the genome of NRRL 47514, a strain associated with Fusarium keratitis outbreak. This study provides the first evidence, to our knowledge, for genomic compartmentalization in two human pathogenic fungal genomes and suggests an important role of LS chromosomes in niche adaptation.