Abstract: A method of fulfilling custom food orders includes obtaining feedback from a user through an ordering application. The feedback relates to a first food item of a first food order following fulfillment of the first food order. The first food item includes a first ingredient. The method includes determining a preferred variation associated with the first ingredient based on the feedback and a first recipe used to make the first food item. The method includes updating a taste profile associated with the user based on the preferred variation. The method includes receiving, from the user, a second food order including a second food item. The method includes retrieving a second recipe associated with the second food item. The method includes selectively modifying the second recipe based on the taste profile. The method includes controlling a food assembly apparatus to prepare the second food item according to the second recipe.

Abstract: Provided herein are methods for altering a health state of a subject by administering a wellness intervention to subjects found to have quantitative measures of microbial genera in the subject's microbiome that are associated with undesirable health states. Undesirable health states can be inferred by executing models that predict health states based on the quantitative measures, such as relative amounts of selected microbial genera to all microbes. Models are created by statistical methods that analyze datasets that include, for each of a plurality of subjects, verified health states and quantitative measures of each of a plurality of microbes classified at designated taxonomic levels, e.g., genus level.

Abstract: A method of fulfilling custom food orders includes obtaining feedback from a user through an ordering application. The feedback relates to a first food item of a first food order following fulfillment of the first food order. The first food item includes a first ingredient. The method includes determining a preferred variation associated with the first ingredient based on the feedback and a first recipe used to make the first food item. The method includes updating a taste profile associated with the user based on the preferred variation. The method includes receiving, from the user, a second food order including a second food item. The method includes retrieving a second recipe associated with the second food item. The method includes selectively modifying the second recipe based on the taste profile. The method includes controlling a food assembly apparatus to prepare the second food item according to the second recipe.

Abstract: Provided herein are methods for altering a health state of a subject by administering a wellness intervention to subjects found to have quantitative measures of microbial genera in the subject's microbiome that are associated with undesirable health states. Undesirable health states can be inferred by executing models that predict health states based on the quantitative measures, such as relative amounts of selected microbial genera to all microbes. Models are created by statistical methods that analyze datasets that include, for each of a plurality of subjects, verified health states and quantitative measures of each of a plurality of microbes classified at designated taxonomic levels, e.g., genus level.

Abstract: Provided herein are methods for altering a health state of a subject by administering a wellness intervention to subjects found to have quantitative measures of microbial genera in the subject's microbiome that are associated with undesirable health states. Undesirable health states can be inferred by executing models that predict health states based on the quantitative measures, such as relative amounts of selected microbial genera to all microbes. Models are created by statistical methods that analyze datasets that include, for each of a plurality of subjects, verified health states and quantitative measures of each of a plurality of microbes classified at designated taxonomic levels, e.g., genus level.

Abstract: One variation of a method for personalizing food orders includes: from a patron, receiving a taste feedback for a first food item in a first food order submitted previously by the patron; predicting an absolute food preference of the patron from the first food order; predicting a relative taste preference of the patron based on the taste feedback and a recipe of the first food item; generating a taste profile of the patron based on the absolute food preference and the relative taste preference; from the patron, receiving a selection for a second food item in a new food order, the second food item different than the first food item; applying the taste profile of the patron to a recipe for the second food item to generate a personalized recipe; and submitting the personalized recipe with the new food order to a robotic food assembly apparatus.

Abstract: One variation of a method for personalizing food orders includes: from a patron, receiving a taste feedback for a first food item in a first food order submitted previously by the patron; predicting an absolute food preference of the patron from the first food order; predicting a relative taste preference of the patron based on the taste feedback and a recipe of the first food item; generating a taste profile of the patron based on the absolute food preference and the relative taste preference; from the patron, receiving a selection for a second food item in a new food order, the second food item different than the first food item; applying the taste profile of the patron to a recipe for the second food item to generate a personalized recipe; and submitting the personalized recipe with the new food order to a robotic food assembly apparatus.

Abstract: One variation of a method for personalizing food orders includes: from a patron, receiving a taste feedback for a first food item in a first food order submitted previously by the patron; predicting an absolute food preference of the patron from the first food order; predicting a relative taste preference of the patron based on the taste feedback and a recipe of the first food item; generating a taste profile of the patron based on the absolute food preference and the relative taste preference; from the patron, receiving a selection for a second food item in a new food order, the second food item different than the first food item; applying the taste profile of the patron to a recipe for the second food item to generate a personalized recipe; and submitting the personalized recipe with the new food order to a robotic food assembly apparatus.

Abstract: The present invention provides a window dressing system which, according to one aspect of the invention, has a bracket for supporting a drapery on one side and a window treatment on the other side. The bracket is configured with tracks which cooperate with movable hardware assemblies attached to the top window treatment and the drapery in a manner that provides simple and efficient removal of the window treatment and the drapery for servicing. The drapery hardware assembly is also designed to facilitate pleating of the drapery in an easy to assemble and disassemble arrangement.