I present a computationally-based representation for indefinite noun phrases and anaphora that models their use in natural language. To this end, three goals for knowledge representation for natural language processing: natural form, conceptual completeness, and structure sharing are described. In addressing these goals, an augmentation to the representation of variables (corresponding to indefinite noun phrases or anaphora) so that variables are not atomic terms is suggested. This leads to an extended, more "natural" representation. It is shown how this representation resolves some representational difficulties with sentences with nonlinear quantifier scoping, in particular, donkey sentences.

A method is proposed for argumentation on the basis of information that characterizes the structure of arguments. The proposed method cein be used both to detect arguments emd to generate candidate arguments for rebuttal. No assumption of a priori knowledge about attack and support relations between propositions, advanced by the agents participating in a dialog, is made. More importantly, by using the method, the relations are dynamically established while the dialog is taking place. This aJlows incremental processing since the agent need only consider the current utterance advanced by the dialog participant, not necessarily the entire argument, to be able to continue processing.

We describe our work on developing a general purpose tutoring system that will allow students to practice their decision-making skills in a number of domains. The tutoring system, B2, supports mixed-initiative natural language interaction. The natural language processing and knowledge representation components aire also general purpose—which leads to a tradeoff between the limitations of superficial processing and syntactic representations and the difficulty of deeper methods and conceptual representations. Our solution is to use a mixed-depth representation, one that encodes syntactic and conceptual information in the same structure. As a result, we can use the same representation framework to produce a detailed representation of requests (which tend to be well-specified) and to produce a partial representation of questions (which tend to require more inference about the context). Moreover, the representations use the same knowledge representation framework that is used to reason about discourse processing and domain information—so that the system can reason with (and about) the utterances, if necessary.

International medical graduates (IMGs) are medical graduates who have received their degree from international medical schools. IMGs must undertake a 3-step process to apply to the National Residency Matching Program match. First, they must obtain a valid standard certificate from the Educational Commission for Foreign Medical Graduates. Following certification, they must apply for and secure a position in a residency training program. Third, they must obtain a visa that would enable them to commence their training. In this article, we delve thoroughly into these stepladders to provide IMGs with a clear roadmap of the process as well as contacts to key agencies that may provide more comprehensive assistance.

Background

Data suggest that pregnant women are not at elevated risk of acquiring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or developing severe disease compared with nonpregnant patients. However, management of pregnant patients who are critically ill with coronavirus disease 2019 (COVID-19) infection is complicated by physiologic changes and other pregnancy considerations and requires balancing maternal and fetal well-being.

Case

We report the case of a patient at 28 weeks of gestation with acute respiratory distress syndrome (ARDS) from COVID-19 infection, whose deteriorating respiratory condition prompted delivery. Our patient's oxygenation and respiratory mechanics improved within hours of delivery, though she required prolonged mechanical ventilation until postpartum day 10. Neonatal swabs for SARS-CoV-2 and COVID-19 immunoglobulin (Ig) G and IgM were negative.

Conclusion

We describe our multidisciplinary management of a preterm pregnant patient with ARDS from COVID-19 infection and her neonate.