Airlines face schedule disruptions daily because of unexpected events, including inclement weather, aircraft mechanical problems, and crew unavailability. These disruptions can cause flight delays and cancellations. As a result, crews may not be in position to service their remaining scheduled flights. Airlines must reassign crews quickly to cover open flights and to return them to their original schedules in a cost-effective manner while honoring all government regulations, contractual obligations, and quality-of-life requirements. CALEB Technologies developed the CrewSolver decision-support system for Continental Airlines to generate globally optimal, or near optimal, crew-recovery solutions. Since its implementation, the system has dealt successfully with several high-profile events, including the December 2000 and March 2001 Nor'easter snowstorms, the June 2001 Houston flood, and most dramatically, the September 11th terrorist attacks. In each case, Continental recovered quickly and obtained overall benefits worth millions of dollars. Continental estimates that in 2001 the CrewSolver system helped it save approximately US $40 million for major disruptions only.

On the NLP4IF 2019 sentence level propaganda classification task, we used a BERT language model that was pretrained on Wikipedia and BookCorpus as team ltuorp ranking #1 of 26. It uses deep learning in the form of an attention transformer. We substituted the final layer of the neural network to a linear real valued output neuron from a layer of softmaxes. The backpropagation trained the entire neural network and not just the last layer. Training took 3 epochs and on our computation resources this took approximately one day. The pre-trained model consisted of uncased words and there were 12-layers, 768-hidden neurons with 12-heads for a total of 110 million parameters. The articles used in the training data promote divisive language similar to state-actor-funded influence operations on social media. Twitter shows state-sponsored examples designed to maximize division occurring across political lines, ranging from "Obama calls me a clinger, Hillary calls me deplorable, … and Trump calls me an American" oriented to the political right, to Russian propaganda featuring "Black Lives Matter" material with suggestions of institutional racism in US police forces oriented to the political left. We hope that raising awareness through our work will reduce the polarizing dialogue for the betterment of nations.

This paper provides an overview of how the social news site Reddit can be used as an example of the ACRL Framework for Information Literacy for Higher Education threshold concept "Authority is Constructed and Contextual." It posits that the construction and context of authority in the sense of Wilson's concept of cognitive authority is in the inherent structure of Reddit and that students can benefit from an example that easily links their personal and academic lives-a connection not always made when discussing authority in peer-reviewed publications or databases.

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Background and Objectives: Virtual intrauterine device (IUD) training options can improve clinician continuing education and patient IUD access. Our objective was to evaluate a virtual, hands-on IUD training for primary care clinicians. Methods: Training sessions occurred via video conferencing and included didactic instruction on IUD eligibility, counseling, placement, and removal. Trainers used pelvic models to demonstrate procedures for all Food and Drug Administration-approved IUDs and guided trainees during hands-on practice with IUDs. Surveys administered before and immediately after training assessed clinician satisfaction and evaluated pre-to-posttraining changes in self-rated comfort level with IUD procedures. We evaluated the changes using Wilcoxon signed-rank sum tests. Results: Thirty-four New Mexico clinicians were trained during 29 sessions from January-June 2021. Trainees (n=32 responding to pre/postsurveys) included nurse practitioners and midwives (48%), physician assistants (28%), physicians (17%), and clinicians in training (7%). Approximately one-third (37%) had previous experience placing IUDs. Elements of training delivery were highly rated by clinicians, with all trainees successfully using the virtual platform and half indicating that they would potentially choose a virtual training over an in-person option in the future. After the training, clinicians reported significantly increased comfort with all aspects of IUD placement and removal (P≤.01). Conclusions: An interactive, virtual IUD training model was highly rated among practicing clinicians and increased their comfort with IUD placement and removal.