238 research outputs found

    Automated Sentiment Analysis for Personnel Survey Data in the US Air Force Context

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    When surveys are distributed across the Air Force (AF), whether it be an employee engagement survey, a climate survey, or similar, significant resources are put towards the development, distribution and analysis of the survey. However, when open ended questions are included on these surveys, respondent comments are generally underutilized, more often treated as a source for pull-quotes rather than a data source in and of themselves. This is due to a lack of transparency and confidence in the accuracy of machine-aided methods such as sentiment analysis and topic modeling. This confidence reduces further when the text has special context, such as within the Air Force context. No model or methodology has been universally identified as ideal for this use case, nor has any model been universally adapted. The inconsistencies in approaches across analytical teams tasked with assessing the results of these surveys leaves data on the field

    Behavioral Use Licensing for Responsible AI

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    Scientific research and development relies on the sharing of ideas and artifacts. With the growing reliance on artificial intelligence (AI) for many different applications, the sharing of code, data, and models is important to ensure the ability to replicate methods and the democratization of scientific knowledge. Many high-profile journals and conferences expect code to be submitted and released with papers. Furthermore, developers often want to release code and models to encourage development of technology that leverages their frameworks and services. However, AI algorithms are becoming increasingly powerful and generalized. Ultimately, the context in which an algorithm is applied can be far removed from that which the developers had intended. A number of organizations have expressed concerns about inappropriate or irresponsible use of AI and have proposed AI ethical guidelines and responsible AI initiatives. While such guidelines are useful and help shape policy, they are not easily enforceable. Governments have taken note of the risks associated with certain types of AI applications and have passed legislation. While these are enforceable, they require prolonged scientific and political deliberation. In this paper we advocate the use of licensing to enable legally enforceable behavioral use conditions on software and data. We argue that licenses serve as a useful tool for enforcement in situations where it is difficult or time-consuming to legislate AI usage. Furthermore, by using such licenses, AI developers provide a signal to the AI community, as well as governmental bodies, that they are taking responsibility for their technologies and are encouraging responsible use by downstream users

    A toolkit for rapid gene mapping in the nematode Caenorhabditis briggsae

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    <p>Abstract</p> <p>Background</p> <p>The nematode <it>C. briggsae </it>serves as a useful model organism for comparative analysis of developmental and behavioral processes. The amenability of <it>C. briggsae </it>to genetic manipulations and the availability of its genome sequence have prompted researchers to study evolutionary changes in gene function and signaling pathways. These studies rely on the availability of forward genetic tools such as mutants and mapping markers.</p> <p>Results</p> <p>We have computationally identified more than 30,000 polymorphisms (SNPs and indels) in <it>C. briggsae </it>strains AF16 and HK104. These include 1,363 SNPs that change restriction enzyme recognition sites (snip-SNPs) and 638 indels that range between 7 bp and 2 kb. We established bulk segregant and single animal-based PCR assay conditions and used these to test 107 polymorphisms. A total of 75 polymorphisms, consisting of 14 snip-SNPs and 61 indels, were experimentally confirmed with an overall success rate of 83%. The utility of polymorphisms in genetic studies was demonstrated by successful mapping of 12 mutations, including 5 that were localized to sub-chromosomal regions. Our mapping experiments have also revealed one case of a misassembled contig on chromosome 3.</p> <p>Conclusions</p> <p>We report a comprehensive set of polymorphisms in <it>C. briggsae </it>wild-type strains and demonstrate their use in mapping mutations. We also show that molecular markers can be useful tools to improve the <it>C. briggsae </it>genome sequence assembly. Our polymorphism resource promises to accelerate genetic and functional studies of <it>C. briggsae </it>genes.</p

    A Multi-surgeon Robotic-guided Thoracolumbar Fusion Experience: Accuracy, Radiation, Complications, Readmissions, and Revisions of 3,874 Screws across Three Robotic Generations

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    Objective Robotic guidance provides indirect visualization of key anatomic landmarks to facilitate minimally invasive surgery (MIS) and is emerging as a reliable and accurate technique for posterior spine instrumentation. We sought to describe eight years of experience with robotic guidance at a high-volume, multi-surgeon center. We hypothesize that robotic guidance will lead to (1) low rates of complication, readmissions, and revision surgery, (2) reduced fluoroscopic radiation exposure, (3) and accurate thoracolumbar instrumentation. Methods A retrospective review of complications, revision surgery, and readmission rates in patients undergoing thoracolumbar fusion surgery utilizing three robotic generations. Secondary analysis was conducted comparing the three robotic generations for complications, revision surgery, accuracy, and readmission rates along with intraoperative fluoroscopic duration. Results A total of 628 patients (3,874 robotic-guided screws) ages 12–81 years-old (43.9% male) were included in the study. At one year, the cumulative complication incidence was 15.5% with a 10.3% incidence of surgical complications (3.7% wound, 1.2% robot-related, and 5.4% non-robot-related complications). At one year, the revision surgery incidence was 9.4%. There was no statistical difference between complications, readmission, or revision surgery after initial admission among the three robotic generations. The average intraoperative fluoroscopic duration was 53.8 seconds (11.9 seconds per screw and 17.6 seconds per instrumented level). Conclusion Robotic guidance in thoracolumbar instrumented fusions was associated with low complication, revision surgery, and readmission rates. Our results suggest robotic guidance can provide accurate guidance with minimal adverse events in thoracolumbar instrumentation
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