Abstract: A document is divided into sections based on a characteristic of the text in the document. Characteristics may include specific characters such as paragraph breaks or selected punctuation, the topics or categories of the text, or a quantity of text in each section. Each section of the document may be represented by an embedding vector in a semantic embedding space. Values are determined based on the text in each section and the semantic characteristics of each section, such as word order, capitalization, punctuation, and word meaning. When a query is received, a vector value representing the query is determined based on the text and semantic characteristics of the query. Based on the similarity between the values determined for the query and those determined for the sections of a document, the specific section of a potentially large document that most closely matches the query is determined and included in a response.

Abstract: A heat pipe has an embedded wick structure that maximizes capillary pumping capability. Heat from attached devices such as integrated circuits evaporates working fluid in the heat pipe. The vapor cools and condenses on a heat dissipation surface. The condensate collects in the wick structure, where capillary pumping returns the fluid to high heat areas.

Abstract: A heat pipe has an embedded wick structure that maximizes capillary pumping capability. Heat from attached devices such as integrated circuits evaporates working fluid in the heat pipe. The vapor cools and condenses on a heat dissipation surface. The condensate collects in the wick structure, where capillary pumping returns the fluid to high heat areas.