Abstract: Systems and methods to select recipes for a customer. A request for at least one recipe is received for a customer. A plurality of questions are dynamically presented to the customer. This dynamic presentation of questions includes: selecting a next question from a dynamic-question-selection data structure based on a previous question presented to the customer and a previous answer received from the customer; presenting the next question to the customer; and receiving a next answer to the next question from the customer. A plurality of recipe attributes associated with the plurality of questions presented to the customer are identified. A group of initial recipes are selected from a plurality of recipes for the customer based on the plurality of recipe attributes. The at least one recipe for the customer is selected from the group of initial recipes and provided to the customer.

Abstract: Systems and methods to dynamically modify recipes for customers based actions while previously preparing other recipes. A first recipe is presented to a customer and images of the customer preparing the first recipe are captured. The images are analyzed to determine an action of the customer. A recipe characteristic associated with the action is determined based on the analysis of the images. A second recipe later selected for the customer, wherein the second recipe includes the determined recipe characteristic. The second recipe is modified to include a modification to the determined recipe characteristic based on the action of the customer when preparing the first recipe, and the modified second recipe is presented to the customer.

Abstract: Systems and methods to predict and optimize automated recipe selection and item delivery for a customer. A server uses an artificial intelligence model to selects a plurality of predicted recipes for a customer based on customer preferences. Different types of constraints are obtained for the customer to generate a plurality of sets of recipes from the predicted recipes and to optimize those sets of recipes for the customer. A specific set of recipes is selected for the customer based on the optimization, and the filling of the order is initiated for the customer with items associated with the selected set of recipes.

Abstract: Systems and methods to predict and optimize automated recipe selection and item delivery for a customer. An item-selection server selects a plurality of predicted recipes based on customer preferences and order history. Hard and soft constraints are obtained to perform the optimization of the predicted recipes. The hard constraints define parameters that cannot be violated by a recipe or set of recipes, and soft constraints define parameters that expresses a tradeoff value associated with a recipe or set of recipes. Optimization includes selecting multiple sets of predicted recipes based on the hard constraints and scoring each recipe set based on the soft constraints, item inventory, and customer preferences. A specific set of recipes is selected for the order based on the scores, and the filling of the order is initiated for the customer with items associated with the selected set of recipes.

Abstract: An automated apparatus and method for configuring and producing packaging for orders of variable configurations of perishable items includes an automatic case erector-sealer; a packing liner dispenser; a cold pack dispenser; a control system; a point of sale ecommerce platform; and a data processor to capture order configuration, order destination, and available order points of origin. The control system captures and uses the order configuration, destination, and delivery date, to generate a time in transit (TNT), total volume, cold volume, and ambient volume, of items in the order. The total volume and cold volume are used to generate a product cube category (PCC). The TNT and the PCC are used to generate a packaging configuration for the order. The system uses the packaging configuration to generate and send operational directives to one or more of the automatic case erector-sealer, the packing liner dispenser, and the cold pack dispenser.

Abstract: Method of producing super soft PAU core-shell copolymer dispersions is a solvent free process. The products have characteristics of both polyurethane and polyacrylate including being non-sticky, having a feeling of touching a peach when touching it by the hand, and having improved adhesion, tensile strength, and toughness.

Abstract: Method of producing super soft PAU core-shell copolymer dispersions is a solvent free process. The products have characteristics of both polyurethane and polyacrylate including non-sticky, having a feeling of touching a peach when touching it by the hand, and improved adhesion, tensile strength, and toughness.

Abstract: A method of producing PUD by a solvent free process includes drying polyol in vacuum; placing the dried polyol and DMBA in a reaction vessel to mix until a first mixture becomes transparent; adding diisocyanate which having functional group of isocyanate(—NCO) to the first mixture to react until —NCO terminated first prepolymer is formed; decreasing temperature of the —NCO terminated first prepolymer to 65° C.; adding a neutralizing agent to the —NCO terminated first prepolymer until —NCO terminated second prepolymer is formed; adding the remaining diisocyanate having isocyanate functional group to the —NCO terminated second prepolymer to form a second mixture; adding deionized water to the second mixture to form prepolymer dispersion; and adding chain extension agent to the prepolymer dispersion to rotate at a range of 200 to 2,000 rpm for chain extension for 1-3 hours until solid content 40.0 wt. % solvent free PUD is produced.

Abstract: A method of producing PUD by a solvent free process includes drying polyol in vacuum; placing the dried polyol and DMBA in a reaction vessel to mix until a first mixture becomes transparent; adding diisocyanate which having functional group of isocyanate (—NCO) to the first mixture to react until —NCO terminated first prepolymer is formed; decreasing temperature of the —NCO terminated first prepolymer to 65° C.; adding a neutralizing agent to the —NCO terminated first prepolymer until —NCO terminated second prepolymer is formed; adding the remaining diisocyanate having isocyanate functional group to the —NCO terminated second prepolymer to form a second mixture; adding deionized water to the second mixture to form prepolymer dispersion; and adding chain extension agent to the prepolymer dispersion to rotate at a range of 200 to 2,000 rpm for chain extension for 1-3 hours until solid content 40.0 wt. % solvent free PUD is produced.