Abstract: A light emitting sealed body includes a housing which stores a discharge gas in an internal space and is provided with a first window portion to which first light is incident and a second window portion from which second light is emitted. The housing includes at least one flow path which is partitioned from the internal space and extends toward at least one of the first window portion and the second window portion.

Abstract: A light emitting sealed body includes: a housing which stores a discharge gas and is provided with a first opening to which first light is incident along a first optical axis and a second opening from which second light is emitted along a second optical axis; a first window portion which hermetically seals the first opening; and a second window portion which hermetically seals the second opening. The housing is formed of a light shielding material which does not transmit the first light and the second light. An internal space is defined by the housing, the first window portion, and the second window portion and the internal space is filled with the discharge gas. The first opening and the second opening are disposed so that the first optical axis and the second optical axis intersect each other.

Abstract: A “Facet Recommender” creates conversational recommendations for facets of particular conversational topics, and optionally for things associated with those facets, from consumer reviews or other social media content. The Facet Recommender applies a machine-learned facet model and optional sentiment-model, to identify facets associated with spans or segments of the content and to determine neutral, positive, or negative consumer sentiment associated with those facets and, optionally, things associated with those facets. These facets are selected by the facet model from a list or set of manually defined or machine-learned facets for particular conversational topic types. The Facet Recommender then generates new conversational utterances (i.e., short neutral, positive or negative suggestions) about particular facets based on the sentiments associated with those facets. In various implementations, utterances are fit to one or more predefined conversational frameworks.

Abstract: A “Facet Recommender” creates conversational recommendations for facets of particular conversational topics, and optionally for things associated with those facets, from consumer reviews or other social media content. The Facet Recommender applies a machine-learned facet model and optional sentiment-model, to identify facets associated with spans or segments of the content and to determine neutral, positive, or negative consumer sentiment associated with those facets and, optionally, things associated with those facets. These facets are selected by the facet model from a list or set of manually defined or machine-learned facets for particular conversational topic types. The Facet Recommender then generates new conversational utterances (i.e., short neutral, positive or negative suggestions) about particular facets based on the sentiments associated with those facets. In various implementations, utterances are fit to one or more predefined conversational frameworks.

Abstract: A “Facet Recommender” creates conversational recommendations for facets of particular conversational topics, and optionally for things associated with those facets, from consumer reviews or other social media content. The Facet Recommender applies a machine-learned facet model and optional sentiment-model, to identify facets associated with spans or segments of the content and to determine neutral, positive, or negative consumer sentiment associated with those facets and, optionally, things associated with those facets. These facets are selected by the facet model from a list or set of manually defined or machine-learned facets for particular conversational topic types. The Facet Recommender then generates new conversational utterances (i.e., short neutral, positive or negative suggestions) about particular facets based on the sentiments associated with those facets. In various implementations, utterances are fit to one or more predefined conversational frameworks.

Abstract: A “Facet Recommender” creates conversational recommendations for facets of particular conversational topics, and optionally for things associated with those facets, from consumer reviews or other social media content. The Facet Recommender applies a machine-learned facet model and optional sentiment-model, to identify facets associated with spans or segments of the content and to determine neutral, positive, or negative consumer sentiment associated with those facets and, optionally, things associated with those facets. These facets are selected by the facet model from a list or set of manually defined or machine-learned facets for particular conversational topic types. The Facet Recommender then generates new conversational utterances (i.e., short neutral, positive or negative suggestions) about particular facets based on the sentiments associated with those facets. In various implementations, utterances are fit to one or more predefined conversational frameworks.

Abstract: One embodiment of an oral airway comprised of two articulating parts which displace the tongue anteriorly and stent open the oropharynx. This device reversibly locks in a conformation which allows it to be used as a conduit for a fiberoptic scope or other airway device. An adjunct to airway management which can be used when mask ventilation or endotracheal intubation is indicated and can be removed easily after intubation without manipulation of the endotracheal tube. Other embodiments are described as shown.

Abstract: One embodiment of an oral airway comprised of two articulating parts which displace the tongue anteriorly and stent open the oropharynx. This device reversibly locks in a conformation which allows it to be used as a conduit for a fiberoptic scope or other airway device. An adjunct to airway management which can be used when mask ventilation or endotracheal intubation is indicated and can be removed easily after intubation without manipulation of the endotracheal tube. Other embodiments are described as shown.