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: 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 scheduling a query for execution. The system receives and parses a query to identify one or more portions of the query. The system determines a resource allocation for each portion of the query, and determines an availability of compute resources for the different portions of the query. Based on the resource allocation and the availability of compute resources, the system schedules the query.

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.