Abstract: A fabric treatment composition having a polymer and a fabric softening active. The polymer includes a cationic repeating unit and a non-cationic repeating unit. The polymer has a weight-average molecular weight of from about 40,000 to about 600,000 Daltons. The polymer has a calculated cationic charge density of from about 0.05 to about 2 meq/g at a pH of between about 2 and about 8. The polymer includes less than about 0.1% by mole of a cross-linking agent. The fabric softening active includes a quaternary ammonium compound. The composition has less than about 5% by weight of the composition of an anionic surfactant.

Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.

Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.

Abstract: The present invention relates to treatment compositions containing polymer systems that provide stability and benefit agent deposition as well as methods of making and using same. Such treatment compositions may be used for example as through the wash and/or through the rinse fabric enhancers as well as unit dose treatment compositions.

Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.

Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.

Abstract: The present invention relates to treatment compositions containing polymer systems that provide stability and benefit agent deposition as well as methods of making and using same. Such treatment compositions may be used for example as through the wash and/or through the rinse fabric enhancers as well as unit dose treatment compositions.

Abstract: An olefin-carboxylic acid copolymer, containing at least one free carboxylic acid side group, or a nitrogen compound quaternized with epoxide in the presence of an olefin-carboxylic acid copolymer, containing at least one free carboxylic acid side group, can be used as a fuel additive or lubricant additive. Processes can be used for preparing additives of this kind and fuels and lubricants additized therewith, such as a detergent additive. These additives, fuels, and lubricants can be used for reduction or prevention of deposits in injection systems of direct injection diesel engines, especially in common rail injection systems; for reduction of fuel consumption of direct injection diesel engines, especially of diesel engines with common rail injection systems; and for minimization of power loss in direct injection diesel engines, especially in diesel engines with common rail injection systems. The additives can also be used for gasoline fuels, especially for operation of DISI engines.

Abstract: A method minimizes power loss in a direct injection diesel engine by adding a copolymer to a diesel fuel composition. The copolymer contains, in a copolymerized form, (A) maleic anhydride, (B) an ?-olefin having from 12 to 30 carbon atoms, (C) optionally an additional aliphatic or cycloaliphatic olefin which has at least 4 carbon atoms and is different from monomer (B), and (D) optionally an additional copolymerizable monomer other than monomers (A), (B) and (C). Monomer (D) can be a vinyl ester, a vinyl ether, a (meth)acrylic ester of an alcohol having at least 5 carbon atoms, an allyl alcohol or an ester thereof, a N-vinyl compound, an ethylenically unsaturated aromatic, an ?,?-ethylenically unsaturated nitrile, a (meth)acrylamide, or an allylamine. Anhydride functionalities present in the copolymer are partly reacted with at least one compound (E) comprising an alcohol group and/or an amino group, and the anhydride functionalities present are hydrolyzed.

Abstract: A computer-implemented method for optimizing electronic content delivery for non-measurable users includes receiving a feature vector for each electronic content impression opportunity, receiving a feature vector for each delivered item of electronic content for measurable users, receiving an in-target indication for each delivered item of electronic content for measurable users, estimating a probability that an electronic content impression opportunity with a specified feature vector will meet targeting requirements based on the received feature vectors and the received in-target indications, receiving an in-target threshold value, generating an in-target rate control signal based on a number of total delivered items of electronic content for measurable users and a number of in-target delivered items of electronic content for measurable users, determining whether the estimated probability is greater than the in-target rate control signal, and generating conditions for delivering a new item of electronic cont

Abstract: The disclosed systems and methods provide a novel framework that provides mechanisms for predicting user actions of provided digital content based on an aggregation of user data. Conventional user tracking, and action prediction and recommendation systems have a lifespan that is ending in the short term due to new privacy laws. The disclosed framework enables personalized recommendations to be formulated for specific users based on an imputation from user data aggregated from a plurality of users. While anonymity is maintained, recommendations for predicted actions can be provided to the users and/or the providers of the content. The disclosed framework can scale the aggregated user data using a Naïve Bayes classifier, from which a logistic regression modeling can be performed to determine the predicted recommendation.

Abstract: Novel compounds can be used as additive packages for improving the cleanliness of direct injection spark ignition (DISI) engines.

Abstract: A lower extremity prosthetic socket, according to some embodiments. The lower extremity prosthetic socket includes a shell having variable thickness along a longitudinal length of the shell. The lower extremity prosthetic socket is configured to provide stability for a residual limb of a user when worn by the user. The lower extremity prosthetic socket is configured to distribute forces. The shell is configured to conform to an anatomical structure of the residual limb of the user.

Abstract: A protective device for an upper extremity post-operative residual limb of a user. The protective device includes a multi-section shell having a shape that corresponds to an anatomical structure of the upper extremity post-operative residual limb of the user. The protective device also includes a hinge coupled with a first section and a second section of the multi-section shell, the hinge configured to facilitate relative rotation of the first section and the second section to transition the protective device between an open configuration and a closed configuration. The multi-section shell is configured to receive one or more attachments to increase functionality of the upper extremity post-operative residual limb of the user.

Abstract: An orthotic device for a patient's foot includes a shell that is configured to structurally support the patient's foot. The shell has a variable thickness along a dimension of the shell. The shell is configured to undergo flexion throughout the shell. The variable thickness of the shell targets areas of increased stress.

Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.

Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.

Abstract: The present invention relates to the use of an olefin-carboxylic acid copolymer, wherein the copolymer comprises at least one free carboxylic acid side group, or of a nitrogen compound quaternized with epoxide in the presence of an olefin-carboxylic acid copolymer, wherein the copolymer comprises at least one free carboxylic acid side group, as a fuel additive or lubricant additive; to processes for preparing additives of this kind, and to fuels and lubricants additized therewith; such as, more particularly, as a detergent additive; for reduction or prevention of deposits in the injection systems of direct injection diesel engines, especially in common rail injection systems, for reduction of the fuel consumption of direct injection diesel engines, especially of diesel engines with common rail injection systems, and for minimization of power loss in direct injection diesel engines, especially in diesel engines with common rail injection systems; and as an additive for gasoline fuels, especially for operation

Abstract: A fabric treatment composition having from about 2.5% to about 20% of a cationic polymer, from about 0.1% to about 20% of a perfume, and a surfactant system, the surfactant system having alkyl polyglucoside, and the composition having less than 5% by weight of an anionic surfactant.

Abstract: An olefin-carboxylic acid copolymer, containing at least one free carboxylic acid side group, or a nitrogen compound quaternized with epoxide in the presence of an olefin-carboxylic acid copolymer, containing at least one free carboxylic acid side group, can be used as a fuel additive or lubricant additive. Processes can be used for preparing additives of this kind and fuels and lubricants additized therewith, such as a detergent additive. These additives, fuels, and lubricants can be used for reduction or prevention of deposits in injection systems of direct injection diesel engines, especially in common rail injection systems; for reduction of fuel consumption of direct injection diesel engines, especially of diesel engines with common rail injection systems; and for minimization of power loss in direct injection diesel engines, especially in diesel engines with common rail injection systems. The additives can also be used for gasoline fuels, especially for operation of DISI engines.