Abstract: Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives raw machine data at an indexing system, and stores at least a portion of the raw machine data in buckets using containerized indexing nodes instantiated in a containerized environment. The data intake and query system stores the buckets in a shared storage system.

Abstract: Systems and methods are described for establishing and managing components of a distributed computing framework implemented in a data intake and query system. The distributed computing framework may include a master and a plurality of worker nodes. The master may selectively operate on a search head captain that is chosen from the search heads of the data intake and query system. The search head captain may distribute configuration information for the master and the distributed computing framework to the other search heads, which in turn, may distribute that configuration information to indexers of the data intake and query system. Worker nodes may be selectively activated for operation on the indexers based on the configuration information, and the worker nodes may additionally use the configuration information to contact the master and join the distributed computing framework.

Abstract: Systems and methods are disclosed for receiving, at a data intake and query system, a query that includes an indication to process data managed by a third-party data storage and processing system that supports a different query language than the data intake and query system. The data intake and query system identifies a third-party data storage and processing system that manages the data to be processed and generates a subquery for execution by the third-party data storage and processing system, generates instructions for one or more worker nodes to receive and process results of the subquery from the third-party data storage and processing system, and instructs the worker nodes to provide results of the processing to the data intake and query system.

Abstract: Systems and methods are described for distributed processing a query in a first query language utilizing a query execution engine intended for single-device execution. While distributed processing provides numerous benefits over single-device processing, distributed query execution engines can be significantly more difficult to develop that single-device engines. Embodiments of this disclosure enable the use of a single-device engine to support distributed processing, by dividing a query into multiple stages, each of which can be executed by multiple, concurrent executions of a single-device engine. Between stages, data can be shuffled between executions of the engine, such that individual executions of the engine are provided with a complete set of records needed to implement an individual stage. Because single-device engines can be significantly less difficult to develop, use of the techniques described herein can enable a distributed system to rapidly support multiple query languages.

Abstract: Systems and methods are disclosed for executing a query that includes an indication to process data managed by an external data system. The system identifies the external data system that manages the data to be processed and generates a subquery for the external data system indicating that the results of the subquery are to be sent to one worker node of multiple worker nodes. The system instructs the one worker node to distribute the results received from the external data system to multiple worker nodes for processing.

Abstract: Disclosed is a data fabric service system that can be implemented in a distributed computer network, such as a data intake and query system. The data index and query system can receive a search query and define a search scheme for applying the search query on distributed data storage systems including internal data storage and external data storage. The data index and query system may provide a portion of the search scheme to a search service of the data fabric service system, which can cause worker nodes of the data fabric service system to perform various functions—including applying the search query to the external data storage based on the portion of the search scheme in order to obtain search results.

Abstract: Systems and methods are described for executing a query of raw machine data that is stored at a remote data store that may store heterogeneous data. The system can determine the directories or file types that may store event data and may instruct one or more worker nodes to access files that may store events based on the determined directories of file types. Further, the system may exclude files at the remote data store that may not be identified as potentially storing events enabling a query that implicates a heterogeneous data store to be efficiently executed.

Abstract: A computer system provides patient monitoring and treatment using implanted biosensors. Data associated with a target joint of a patient is collected via one or more implanted biosensors. A plurality of feature values are extracted from the data. The plurality of feature values are processed using a trained classification model to select a recommendation. The recommendation is provided to mitigate hemophilia-related injury to the target joint. Embodiments of the present invention further include a method and program product for providing patient monitoring and treatment using implanted biosensors in substantially the same manner described above.

Abstract: A method, computing system, and computer program product are provided. Items at a source location are detected and classified, with respect to fragility and perishability, based on characteristics of the each respective item and is performed by trained machine learning models. Item boundaries are predicted based on applying respective data regarding points on a surface of the each respective item to a trained second machine learning model to predict the item boundaries. The each respective item is classified into a respective group with respect to an available volume of the cargo space based on sensor data of the cargo space, the classified fragility and perishability, the predicted item boundaries, and a third machine learning model. An arrangement of the items in the cargo space is determined based on the group classifications and a corresponding destination location associated with the each respective item and is visualized relative to the cargo space.

Abstract: The invention provides a method of preparing a silica-protein sub-micron particle, the method comprising contacting, in an aqueous medium having a pH in the range of about 7.5 to 10 and having an ionic strength in the range of about 1.2 to 60 mM, (i) protein sub-micron particle cores comprising 0.2 to 3 ?moles, per mg of the protein sub-micron particle cores, of a basic compound of formula (I) or an ester and/or amide thereof wherein n is an integer selected from 1 to 10, and p is an integer selected from 1 to 3, with (ii) orthosilicic acid or an ester thereof, in an amount equivalent to 5 to 60% (w/w) orthosilicic acid per mg of the protein sub-micron particle cores, to form the silica-protein sub-micron particle. The invention also provides a method of making a GLP-1 receptor agonist sub-micron particle core, by a. contacting a peptide in an aqueous medium at a pH of about 5.0-8.0 and comprising about 0.3-1.

Abstract: A method, computer system, and a computer program product for impact response is provided. The present invention may include triggering a stimulus if a threshold is reached or exceeded based on a positional relationship between a body suit and a single-track vehicle, wherein the stimulus activates one or more pressure sensors of the body suit. The present invention may include generating a pressure map of the body suit utilizing the one or more pressure sensors. The present invention may include generating an injury map using a machine learning model, wherein the injury map is based on the pressure map and one or more input parameters, and wherein the input parameters are specific to a user of the body suit.

Abstract: In an approach to smart joint monitoring for bleeding disorder patients, one or more sets of data are received from a smart joint monitor, where the smart joint monitor includes one or more sensors. One or more criticalities are detected, where the one or more criticalities are detected by an artificial intelligence engine based on the one or more sets of data and a global knowledge base. One or more suggestions are determined, where the one or more suggestions are determined by the artificial intelligence engine based on the one or more criticalities and the global knowledge base.

Abstract: A method, computing system, and computer program product are provided. Items at a source location are detected and classified, with respect to fragility and perishability, based on characteristics of the each respective item and is performed by trained machine learning models. Item boundaries are predicted based on applying respective data regarding points on a surface of the each respective item to a trained second machine learning model to predict the item boundaries. The each respective item is classified into a respective group with respect to an available volume of the cargo space based on sensor data of the cargo space, the classified fragility and perishability, the predicted item boundaries, and a third machine learning model. An arrangement of the items in the cargo space is determined based on the group classifications and a corresponding destination location associated with the each respective item and is visualized relative to the cargo space.