Abstract: The present invention relates to methods for producing oxygenated terpenoids. Polynucleotides, derivative enzymes, and host cells for use in such methods are also provided.

Abstract: Techniques for monitoring packet telemetry are provided. A policy is received at a first node from a controller, where the policy includes an indication of a first flow. A first packet belonging to the first flow is received at the first node. A second node in a network path for the first packet is determined. A first header is added to the first packet based on the policy, wherein the first header includes an indication of the controller. The first packet is transmitted to the second node. Finally, telemetry data associated with the first node is transmitted to the controller based on the policy.

Abstract: In an example embodiment, training data is obtained, the training data comprising values for a plurality of different features. Then a global machine learned model is trained using a first machine learning algorithm by feeding the training data into the first machine learning algorithm during a fixed effect training process. A non-linear first random effects machine learned model is trained by feeding a subset of the training data into a second machine learning algorithm, the subset of the training data being limited to training data corresponding to a particular value of one of the plurality of different features.

Abstract: In various aspects and embodiments, the invention relates to bacterial strains and methods for making terpene and terpenoid products. The invention provides bacterial strains with improved carbon flux through the MEP pathway, to thereby increase terpene and/or terpenoid product yield by fermentation with carbon sources such as glucose.

Abstract: The present subject matter described herein relates to a Magnetically Augmented Plasmonic Tweezer (MAPT), a method for fabrication of the MAPT, and a method for trapping and maneuvering one or more colloidal particles inside a fluid. The fluid may correspond to a fluid inside a microfluidic device or a biological fluid. The MAPT can comprise a helical support structure to provide maneuverability in fluid. Further, a magnetic component is integrated in the MAPT for motion control. Plasmonic nanostmctures are integrated in the MAPT for optical trapping of particles.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to Future Connection Engine that generates a select pairing of member accounts for a potential social network connection. The Future Connection Engine predicts, according to the prediction model, a first number of subsequent social network connections for a first member account in the select pairing that will occur after establishing the potential social network connection and a second number of subsequent social network connections for a second member account in the select pairing that will occur after establishing the potential social network connection. The Future Connection Engine generates connection recommendations for display to the select pairing based on whether the first and/or the second number of subsequent social network connections satisfies a threshold.

Abstract: The present disclosure relates to methods for producing oxygenated terpenoids, and preparation of compositions and formulations thereof. Polynucleotides, derivative enzymes, and host cells for use in such methods are also provided.

Abstract: In an example, first and second machine learned models corresponding to a particular context of a social networking service are obtained, the first machine learned model trained via a first machine learning algorithm to output an indication of importance of a social networking profile field to obtaining results in the particular context, and the second machine learned model trained via a second machine learning algorithm to output a propensity of the user to edit a social networking profile field if requested. One or more missing fields in a social networking profile for the user are identified. For each of one or more of the one or more missing fields, the field and an identification of the user are passed through the first and second machine learned models, and outputs of the first and second machine learned models are combined to identify one or more top missing profile fields.

Abstract: In various aspects and embodiments, the invention relates to bacterial strains and methods for making terpene and terpenoid products. The invention provides bacterial strains with improved carbon flux through the MEP pathway, to thereby increase terpene and/or terpenoid product yield by fermentation with carbon sources such as glucose.

Abstract: Techniques for monitoring packet telemetry are provided. A policy is received at a first node from a controller, where the policy includes an indication of a first flow. A first packet belonging to the first flow is received at the first node. A second node in a network path for the first packet is determined. A first header is added to the first packet based on the policy, wherein the first header includes an indication of the controller. The first packet is transmitted to the second node. Finally, telemetry data associated with the first node is transmitted to the controller based on the policy.

Abstract: Machine learning techniques for multi-objective content item selection are provided. In one technique, resource allocation data is stored that indicates, for each campaign of multiple campaigns, a resource allocation amount that is assigned by a central authority. In response to receiving the content request, a subset of the campaigns is identified based on targeting criteria. Multiple scores are generated, each score reflecting a likelihood that a content item of the corresponding campaign will be selected. Based on the scores, a particular campaign from the subset is selected and the corresponding content item transmitted over a computer network to be displayed on a computing device. A resource allocation amount that is associated with the particular campaign is identified. A resource reduction amount associated with displaying the content item of the particular campaign is determined. The particular resource allocation is reduced based on the resource reduction amount.

Abstract: The present disclosure relates to methods for producing oxygenated terpenoids, and preparation of compositions and formulations thereof. Polynucleotides, derivative enzymes, and host cells for use in such methods are also provided.

Abstract: A plurality of potential feed objects and corresponding identifications of actors who performed a user interface action that caused a corresponding potential feed object to be generated are obtained. The plurality of potential feed objects and corresponding actor identifications are then fed into a machine learned feed object ranking model, with the machine learned feed object ranking model having been trained via a machine learning algorithm to calculate a score for each of the potential feed objects. The score is based on a combination of a likelihood that the user will perform an interaction, via the user interface, on the potential feed object, likelihood that the user's interaction will cause one or more downstream events by other users, and likelihood that a response from a viewer will cause the actor corresponding to the potential feed object to perform an additional user interface action to generate another potential feed object.

Abstract: In an example, a plurality of potential feed objects are obtained. An identification of a user performing a navigation command in a user interface is also obtained, the navigation command causing a feed to be displayed or updated. The identification of the user and the plurality of potential feed objects are fed to a machine learned feed object ranking model, the feed object ranking model having been trained via a machine learning algorithm to calculate a score for each of the potential feed objects, the score being based on a combination of a likelihood that the user will perform an interaction, via the user interface, on the potential feed object, likelihoods that the user's interaction will cause one or more downstream events by other users, and a value of the one or more downstream events to a social networking service. The plurality of feed objects are ranked by their scores.

Abstract: In an example, first and second machine learned models corresponding to a particular context of a social networking service are obtained, the first machine learned model trained via a first machine learning algorithm to output an indication of importance of a social networking profile field to obtaining results in the particular context, and the second machine learned model trained via a second machine learning algorithm to output a propensity of the user to edit a social networking profile field if requested. One or more missing fields in a social networking profile for the user are identified. For each of one or more of the one or more missing fields, the field and an identification of the user are passed through the first and second machine learned models, and outputs of the first and second machine learned models are combined to identify one or more top missing profile fields.

Abstract: Methods, systems, and computer programs are presented for identifying tuning parameters for mixing items in different categories for a user feed. One method includes maximizing utilities when presenting feeds to social network users, each utility having a weight for mixing items. The method further includes identifying a utilities maximization goal such that a first utility is maximized while other utilities are above a threshold, and initializing a counter. A loop, repeated until convergence, includes generating sample weights; performing an experiment with the sample weights for i users and j feed sessions to determine utility action indicators; for each utility, estimating a posterior distribution of an underlying hyperfunction and drawing samples; for each drawn sample, calculating a utility function and the weight that maximizes the utility function; generating an empirical distribution based on the sample weights; and incrementing the counter. The identified weights are utilized for creating the feeds.

Abstract: The disclosed embodiments provide a system for facilitating interaction within a social network. During operation, the system obtains a set of attributes of a social network of a first member and a set of historic interactions in the social network. Next, the system analyzes the attributes and the historic interactions to predict an effect of a potential interaction between the first member and a second member of the social network on subsequent interactions in the social network. The system then uses the predicted effect to generate output for modulating the subsequent interactions in the social network.

Abstract: The present disclosure relates to methods for producing oxygenated terpenoids, and preparation of compositions and formulations thereof. Polynucleotides, derivative enzymes, and host cells for use in such methods are also provided.

Abstract: A method for directly writing metal traces on a wide range of substrate materials is disclosed. The method includes writing a pattern of particle-free metal-salt-based ink on the substrate followed by a plasma-based treatment to remove the non-metallic components of the ink and decompose its metal salt into pure metal. The ink is based on a multi-part solvent whose components differ in at least one of evaporation rate, surface tension, and viscosity, which improves the manner in which the ink is converted into its metal constituent via the plasma treatment. In some embodiments, a microplasma is used for post-treatment of the deposited ink, where the plasma properties are controlled to provide different material properties, such as porosity and effective resistivity, in different regions of the metal pattern.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to Future Connection Engine that generates a select pairing of member accounts for a potential social network connection. The Future Connection Engine predicts, according to the prediction model, a first number of subsequent social network connections for a first member account in the select pairing that will occur after establishing the potential social network connection and a second number of subsequent social network connections for a second member account in the select pairing that will occur after establishing the potential social network connection. The Future Connection Engine generates connection recommendations for display to the select pairing based on whether the first and/or the second number of subsequent social network connections satisfies a threshold.