Abstract: A method for managing applications includes obtaining, by a client in a customer environment, an upgrade issue report for the application, making a first determination that a resynchronization of a client self-healing classification model with the production host environment (PHE) self-healing classification model is required, wherein the PHE self-healing classification model is stored in the PHE, performing the resynchronization with the PHE self-healing classification model to obtain a synchronized client self-healing classification model, applying the synchronized client self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report, making a second determination that the state indicates a self-healable state, based on the second determination, performing a self-healing process on the application based on the upgrade issue report, and storing a resolution report based on results of the self-healing process, wherein the PHE is operatively connected to the custome

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for utilizing focused aggregation of classification model outputs to classify variable length documents. For instance, the disclosed systems can utilize a classification model to determine category scores for segments from an electronic document. Furthermore, the disclosed systems can identify positive trigger segments from the segments by comparing the category scores to a threshold category score. Moreover, the disclosed systems can determine a positive trigger ratio for the target category based on the positive trigger segments and the segments. Additionally, the disclosed systems can generate an aggregated category score for the electronic document from the positive trigger segments (when the positive trigger ratio satisfies a threshold positive trigger ratio) and distribute the electronic documents to client devices based on the aggregated category score.

Abstract: A framework in which annotated images can be analyzed in small batches to learn and distinguish between higher-quality annotations and lower-quality annotations, especially in the case of manual annotations for which quality assurance is desired. This framework is extremely generalizable and can be used for indoor images, outdoor images, medical images, etc., without limitation. An echo state network (ESN) is provided as a special case of semantic segmentation model that can be trained using as few as tens of annotated images to predict semantic regions and provide metrics that can be used to distinguish between higher-quality annotations and lower-quality annotations.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for dynamically augmenting relevance rankings using data from external ratings sources.

Abstract: Techniques for integrating freshness and relevance within a programmatic relevance service are discussed herein. Some embodiments may include a relevance service system, including one or more batch processors and one or more online processors. The one or more batch processors may be configured to track message recipient behavior from electronic clickstream data, and generate models of functions that predict access probability for individual users. The one or more online processors may use the access probability calculated in batch to facilitate on demand deal ranking adjustments that account for freshness as informed by the predicted access probability for communications sent to the user.

Abstract: A method for managing upgrades of components of clients includes obtaining an upgrade failure prediction request associated with a client of the clients, and in response to obtaining an update failure prediction request: obtaining live data associated with the client, matching the live data with a training data cluster, selecting relevant features associated with processed training data of the training data cluster, generating an upgrade failure prediction using the live data associated with the relevant features and a prediction model, making a determination that the upgrade failure prediction implicates an action is required, and based on the determination, initiating performance of the action.

Abstract: Modified ribosomes that were selected using a dipeptidyl-puromycin aminonucleoside are used to mediate site-specific incorporation of one or more peptides and peptidomimetics into protein in a cell free translation system. In addition, new fluorescent dipeptidomimetics have been synthesized and incorporated into proteins, as well as modified proteins containing one or more non-naturally occurring dipeptides.

Abstract: Multikinase degraders described herein contain on one end a Von Hippel-Lindau (VHL) E3 ligase ligand or cereblon E3 ligase recruiter moiety, which bind to the VHL or cereblon E3 ubiquitin ligase (defined as a ubiquitin ligand binding moiety or ULM group), respectively, and on the other end a promiscuous kinase ligand that binds a target protein kinase (defined as a protein/polypeptide targeting moiety or PTM group), such that the target protein is in close proximity to the ubiquitin ligase. This leads to the ubiquitination and subsequent degradation (and inhibition) of the target protein. Specific present multikinase degraders as shown bind about 360 out of 400 tested kinases, showing that they are much more general kinase binders and degraders than any previously reported.

Abstract: A framework in which annotated images can be analyzed in small batches to learn and distinguish between higher-quality annotations and lower-quality annotations, especially in the case of manual annotations for which quality assurance is desired. This framework is extremely generalizable and can be used for indoor images, outdoor images, medical images, etc., without limitation. An echo state network (ESN) is provided as a special case of semantic segmentation model that can be trained using as few as tens of annotated images to predict semantic regions and provide metrics that can be used to distinguish between higher-quality annotations and lower-quality annotations.

Abstract: A method for managing applications in a production host environment includes obtaining, by an application upgrade management system, an upgrade issue report for the application, applying a self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report, making a determination that the state indicates a self-healable state, based on the determination, performing a self-healing process on the application based on the upgrade issue report, and storing a resolution report based on results of the self-healing process.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving an input to register a device for tracking, the input comprising registration data specifying the device and one or more components in the device to register for tracking and a minimum acceptance criterion for each of the one or more components, the minimum acceptance criterion for a registered component defines a minimum threshold percentage of votes needed to approve a modification to the registered component. The method also includes recording the device identifier and the registration data related to the device in a device ledger, generating a rule execution set for the device ledger, the rule execution set comprising one or more rules pertaining to approval of requests to modify the device, and processing requests to modify the device or the one or more registered components in the device based on the specified minimum acceptance criterion and the rule execution set.

Abstract: A method comprises receiving a notification of an issue with at least one component of a plurality of components in a computing environment. One or more machine learning algorithms are used to determine one or more components of the plurality of components impacted by the issue with the at least one component. The method further comprises collecting operational data for the at least one component and the one or more impacted components.

Abstract: A processor comprising an instruction execution circuit to execute a second code stored at a second address of a memory, wherein the second code is translated from a first code stored at a first address of the memory and a translation table (TT) controller coupled to a translation table to store a TT entry comprising a mapping between the first address and the second address and an attribute field comprising an attribute value associated with execution of the second code, wherein the TT controller is to monitor execution of the second code by the instruction execution circuit and update, based on a performance metric of the execution, the attribute value of the TT entry.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a universal relevance service framework for ranking and personalizing items.

Abstract: The invention relates to a method of making parts of construction materials by using a mold coated with multiple resin-based layers comprising at least an epoxy resin-based primer and a polyurethane resin-based demolding layer, wherein the mold can be used for multiple cycles after curing and demolding. The invention also relates to the resin-coated mold and the cured parts of construction materials having smooth surface made thereof.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for a universal relevance service framework for ranking and personalizing items.

Abstract: Systems, methods and techniques disclosed herein provide dynamic time-based adjustment of predictive modeling data.

Abstract: A vehicle control method and system, including: receiving road friction information indicating road friction estimates for a plurality of regions surrounding the vehicle; detecting and determining a predicted trajectory for an object within the plurality of regions surrounding the vehicle; wherein the predicted trajectory for the object is determined based in part on the road friction estimates for the plurality of regions surrounding the vehicle; and modifying operation of the vehicle based on the predicted trajectory for the object. The predicted trajectory for the object is determined based in part on a risk map for the plurality of regions surrounding the vehicle that is generated from a road friction map for the plurality of regions surrounding the vehicle.

Abstract: The present disclosure provides systems, methods, and metrics that filter out online visitor behavioral data that represents a potential lead with a high likelihood to convert to a vehicle sale from online visitor behavioral data that does not represent a potential lead with a low likelihood to convert to a vehicle sale, based on a mapping of sales back to observed website and vehicle configurator data. This enables more effective lead generation and the more efficient targeting of online incentive offers and sales “nudges,” for example. Further, the present disclosure enables web analytics data to be combined with sales data for sales forecasting in general.

Abstract: A method and system operable for: receiving a search query including search terms; using a machine learning module, selecting features of the search terms and mapping an association between the search terms and a domain object, thereby generating a domain object classification; tagging the domain object with the domain object classification; and using the domain object tagged with the domain object classification to conduct a subsequent search. Conducting the subsequent search includes: receiving a subsequent search query including subsequent search terms; tokenizing the subsequent search terms; finding permutations of the tokenized subsequent search terms; matching the subsequent search terms to the domain object tagged with the domain object classification; and displaying subsequent search results via a user interface.