Abstract: A computer-executable method, a computer system and a non-transitory computer-readable medium are provided for causing electronic marketing communications of one or more promotions to be generated on a mobile computing device associated with a consumer. A method includes programmatically retrieving promotion data indicative of a plurality of promotions from a computer memory. The method includes determining, using processing circuitry, a promotion score for each of the plurality of promotions. Each promotion score is determined based on consumer profile data, stored consumer activity data, and at least one of: current consumer activity data, current local context data, or predicted consumer activity data. The method further includes outputting indications configured to generate electronic marketing communications associated with the plurality of promotions based on the promotion scores of the plurality of promotions.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system based on an analysis of previous consumer behavior. One aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving data representing a user, the data including user identification and historical data; receiving a set of promotions recommended for the user; assigning the user to a consumer lifecycle model state based in part on the historical data and the user identification; selecting a ranking algorithm associated with the consumer lifecycle model state; and ranking the received set of promotions based on a predicted promotion relevance value associated with each promotion, the predicted promotion value being calculated using the ranking algorithm.

Abstract: Examples for handling ownership of process threads include acquiring ownership of a set of process threads to assign ownership of a subject process thread to an ownership agent. In some examples, acquiring ownership may include acquiring ownership of process threads with a wait event. During acquiring ownership of the set of process threads, one or more process threads that are acquired may be released to attend to an event that has occurred. A thread coordinator that handles ownership during acquiring phase may release and rebid one or more process threads. Upon acquiring all the process threads, the ownership of the subject process thread is assigned to an ownership agent. With a set of ownership conditions, the process threads are acquired efficiently within reduced time and with reduced deadlocks.

Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology evaluates naturally occurring proteins by a process that is done partly in silico and partly by empirical evaluation. A database is created in which each individual protein is characterized by vector representations of structural and functional features. Clusters of individual proteins are formed by pairwise comparison of each protein's vector representation, adjusting the degree of similarity used to define clusters until a desired number of clusters are obtained. A protein representative is selected from each cluster for evaluation by high-throughput expression and laboratory testing for a particular food function. High scoring representatives identify clusters that can be mined for additional protein candidates. Multiple cycles of the machine learning, database mining, expression and testing yield ingredients suitable for assessment as part of a commercial food product.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system using predictive models derived from tiered feature data.

Abstract: This disclosure provides a technology for developing individual proteins for use in industrial processes that include food production. The technology mines sequence data from protein databases by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression, and testing are done to yield potential ingredients suitable for use in the production of foods, cosmetics, agricultural feed, pharmaceutical excipients, and other industrial products.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media configured to use a per-set level optimization of the rank order of promotions to be recommended to a consumer. In some embodiments, machine learning is used offline to generate a predictive diversity model that receives one or more similarity rank features associated with a promotion (e.g., category, price band) as input, and produces an output multiplier to be applied to the promotion's respective associated relevance score (e.g., a relevance score representing a prediction of the promotion's conversion rate without diversity features). At run time, per-set optimization of the ordering of a set of promotions is implemented by adjusting the respective associated relevance scores of the promotions using the diversity model and then re-ordering the set of promotions based on their respective adjusted relevance scores.

Abstract: A blanket suspender assembly for suspending a blanket around pants of a user includes a blanket and a suspender. A strip is coupled along a full length of a top edge of the blanket. The strip is a first portion of a hook and loop fastener. The suspender comprises of a pair of straps. Each strap of the pair of straps has a front hinge and a back hinge. The suspender is placed on the shoulders of a user where the front fringe of each strap is positioned in front of the user and the back fringe of each strap is positioned behind the user. A plurality of tabs is coupled to a respective one of each front hinge and each back hinge. Each of the tabs is the second portion of the hook and loop fastener. Each of the tabs engages by hook and loop fastening with the strip.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system based on an analysis of previous consumer behavior. One aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving data representing a user, the data including user identification and historical data; receiving a set of promotions recommended for the user; assigning the user to a consumer lifecycle model state based in part on the historical data and the user identification; selecting a ranking algorithm associated with the consumer lifecycle model state; and ranking the received set of promotions based on a predicted promotion relevance value associated with each promotion, the predicted promotion value being calculated using the ranking algorithm.

Abstract: A blanket suspender assembly for suspending a blanket around pants of a user includes a blanket and a suspender. A strip is coupled along a full length of a top edge of the blanket. The strip is a first portion of a hook and loop fastener. The suspender comprises of a pair of straps. Each strap of the pair of straps has a front hinge and a back hinge. The suspender is placed on the shoulders of a user where the front fringe of each strap is positioned in front of the user and the back fringe of each strap is positioned behind the user. A plurality of tabs is coupled to a respective one of each front hinge and each back hinge. Each of the tabs is the second portion of the hook and loop fastener. Each of the tabs engages by hook and loop fastening with the strip.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers.

Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology mines sequence data by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression, and testing are done to yield potential ingredients suitable for assessment as part of a commercial food product.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a predictive recommendation system based on an analysis of previous consumer behavior. One aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving data representing a user, the data including user identification and historical data; receiving a set of promotions recommended for the user; assigning the user to a consumer lifecycle model state based in part on the historical data and the user identification; selecting a ranking algorithm associated with the consumer lifecycle model state; and ranking the received set of promotions based on a predicted promotion relevance value associated with each promotion, the predicted promotion value being calculated using the ranking algorithm.

Abstract: Examples for handling ownership of process threads include acquiring ownership of a set of process threads to assign ownership of a subject process thread to an ownership agent. In some examples, acquiring ownership may include acquiring ownership of process threads with a wait event. During acquiring ownership of the set of process threads, one or more process threads that are acquired may be released to attend to an event that has occurred. A thread coordinator that handles ownership during acquiring phase may release and rebid one or more process threads. Upon acquiring all the process threads, the ownership of the subject process thread is assigned to an ownership agent. With a set of ownership conditions, the process threads are acquired efficiently within reduced time and with reduced deadlocks.

Abstract: Visible spectrum quantum dot (QD) light emitting sources integrable with integrated silicon photonics include a plurality of epitaxially grown InP QDs within an active region. The light emitting sources include light emitting diodes (LEDs) and semiconductor lasers.

Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology mines natural sources by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression and testing are done to yield potential ingredients suitable for assessment as part of a commercial food product.

Abstract: A computer-executable method, a computer system and a non-transitory computer-readable medium are provided for causing electronic marketing communications of one or more promotions to be generated on a mobile computing device associated with a consumer. A method includes programmatically retrieving promotion data indicative of a plurality of promotions from a computer memory. The method includes determining, using processing circuitry, a promotion score for each of the plurality of promotions. Each promotion score is determined based on consumer profile data, stored consumer activity data, and at least one of: current consumer activity data, current local context data, or predicted consumer activity data. The method further includes outputting indications configured to generate electronic marketing communications associated with the plurality of promotions based on the promotion scores of the plurality of promotions.