Abstract: An endpoint computer system can harvest data relating to a plurality of events occurring within an operating environment of the endpoint computer system and can add the harvested data to a local data store maintained on the endpoint computer system. A query response can be generated, for example by identifying and retrieving responsive data from the local data store. The responsive data are related to an artifact on the endpoint computer system and/or to an event of the plurality of events. In some examples, the local data store can be an audit log and/or can include one or more tamper resistant features. Systems, methods, and computer program products are described.

Abstract: An endpoint computer system can harvest data relating to a plurality of events occurring within an operating environment of the endpoint computer system and can add the harvested data to a local data store maintained on the endpoint computer system. In some examples, the local data store can be an audit log and/or can include one or more tamper resistant features. Systems, methods, and computer program products are described.

Abstract: The present invention discloses polyglycol epoxide crosslinked sodium hyaluronate gel for injection and a preparation method thereof. A polyglycol epoxide is a compound with single molecular weight preferably; a plurality of ether bonds are present in the molecule of the polyglycol epoxide, the water solubility is good, and thus, the polyglycol epoxide is more easily subjected to a crosslinking reaction with polysaccharides; and meanwhile, polyglycol is relatively easy in adjustment of the number of repeating units and relatively easy in control of length, and thus, the sodium hyaluronate gel prepared by taking the polyglycol epoxide as a crosslinker is relatively easy in regulation and control of properties. The crosslinked sodium hyaluronate gel is low in toxicity, little in residual, small in squeezing and pushing force, good in shaping performance, good in enzyme resistance and long in in-vivo retention time. The present invention further discloses a mild crosslinker deactivation technology.

Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: Determining, by a machine learning model in an isolated operating environment, whether a file is safe for processing by a primary operating environment. The file is provided, when the determining indicates the file is safe for processing, to the primary operating environment for processing by the primary operating environment. When the determining indicates the file is unsafe for processing, the file is prevented from being processed by the primary operating environment. The isolated operating environment can be maintained on an isolated computing system remote from a primary computing system maintaining the primary operating system. The isolating computing system and the primary operating system can communicate over a cloud network.

Abstract: An apparatus configured to be worn on a head of a user, includes: a screen configured to present graphics to the user; a camera system configured to view an environment in which the user is located; and a processing unit configured to determine a map based at least in part on output(s) from the camera system, wherein the map is configured for use by the processing unit to localize the user with respect to the environment; wherein the processing unit of the apparatus is also configured to obtain a metric indicating a likelihood of success to localize the user using the map, and wherein the processing unit is configured to obtain the metric by computing the metric or by receiving the metric.

Abstract: The present invention discloses a PEGylated thioxanthone photoinitiator and a photosensitive resin composition, the PEGylated thioxanthone compound is eco-friendly and has low toxicity, high initiation efficiency and good thermal stability, meanwhile, as a kind of photoinitiator, the compound has a small amount of fragment residue after cured, and may improve the compatibility of the photoinitiator and photosensitive resin composition system. The photosensitive resin composition provided by the present invention has reasonable allocation of ingredients and content in the components thereof, capable of 3D-printing a hydrogel having a specific structure; the hydrogel has lower cytotoxicity and better biocompatibility, and may applied in bioengineering fields, e.g., 3D cell culture.

Abstract: A method of training a reinforcement machine learning computer system. The method comprises providing a machine-learning computer programming language including a pre-defined plurality of reinforcement machine learning criterion statements, and receiving a training specification authored in the machine-learning computer programming language. The training specification defines a plurality of training sub-goals with a corresponding plurality of the reinforcement machine learning criterion statements supported by the machine-learning computer programming language. The method further comprises computer translating the plurality of training sub-goals from the training specification into a shaped reward function configured to score a reinforcement machine learning model configuration with regard to the plurality of training sub-goals.

Abstract: A system form localizing an electronic device with dynamic buffering identifies, from the buffer, a first set of features that is extracted from a first image captured by the electronic device and receives, at the system, a second set of features that is extracted from a second image captured by the electronic device. The system further determines a first characteristic for the first set of features and a second characteristic for the second set of features and determines whether a triggering condition for dynamically changing a size of the buffer is satisfied based at least in part upon the first characteristic for the first set of features and the second characteristic for the second set of features.

Abstract: A cross reality system enables any of multiple devices to efficiently access previously stored maps. Both stored maps and tracking maps used by portable devices may have any of multiple types of location metadata associated with them. The location metadata may be used to select a set of candidate maps for operations, such as localization or map merge, that involve finding a match between a location defined by location information from a portable device and any of a number of previously stored maps. The types of location metadata may prioritized for use in selecting the subset. To aid in selection of candidate maps, a universe of stored maps may be indexed based on geo-location information. A cross reality platform may update that index as it interacts with devices that supply geo-location information in connection with location information and may propagate that geo-location information to devices that do not supply it.

Abstract: A system is provided for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: In one respect, there is provided a system for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: An augmented reality viewing system is described. A local coordinate frame of local content is transformed to a world coordinate frame. A further transformation is made to a head coordinate frame and a further transformation is made to a camera coordinate frame that includes all pupil positions of an eye. One or more users may interact in separate sessions with a viewing system. If a canonical map is available, the earlier map is downloaded onto a viewing device of a user. The viewing device then generates another map and localizes the subsequent map to the canonical map.

Abstract: The disclosure discloses a dendritic polyethylene glycol derivative and a preparation method and an application thereof. The dendritic polyethylene glycol derivative has a structure of formula (I), has multiple end functional groups, has a stronger water solubility in comparison with linear-chain polyethylene glycol, and can solve a problem of insufficient water solubility due to the increase of load when modifying an insoluble drug by the polyethylene glycol. The preparation method of the dendritic polyethylene glycol derivative provided by the disclosure has mild reaction conditions, is green and environmentally friendly, is low in cost, and is easy to implement industrialization.

Abstract: A cross reality system enables any of multiple devices to efficiently and accurately access previously stored maps and render virtual content specified in relation to those maps. The cross reality system may include a cloud-based localization service that responds to requests from devices to localize with respect to a stored map. The request may include one or more sets of feature descriptors extracted from an image of the physical world around the device. Those features may be posed relative to a coordinate frame used by the local device. The localization service may identify one or more stored maps with a matching set of features. Based on a transformation required to align the features from the device with the matching set of features, the localization service may compute and return to the device a transformation to relate its local coordinate frame to a coordinate frame of the stored map.

Abstract: A cross reality system enables any of multiple types of devices to efficiently and accurately access previously stored maps and render virtual content specified in relation to those maps. The cross reality system may include a cloud-based localization service that responds to requests from devices to localize with respect to a stored map. Devices of any type, with native hardware and software configured for augmented reality operations may be configured to work with the cross reality system by incorporating components that interface between the native AR framework of the device and the cloud-based localization service. These components may present position information about the device in a format recognized by the localization service. Additionally, these components may filter or otherwise process perception data provided by the native AR framework to increase the accuracy of localization.

Abstract: An augmented reality viewing system is described. A local coordinate frame of local content is transformed to a world coordinate frame. A further transformation is made to a head coordinate frame and a further transformation is made to a camera coordinate frame that includes all pupil positions of an eye. One or more users may interact in separate sessions with a viewing system. If a canonical map is available, the earlier map is downloaded onto a viewing device of a user. The viewing device then generates another map and localizes the subsequent map to the canonical map.

Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more instruction sequences. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: training, based at least on training data, a machine learning model to detect one or more predetermined interdependencies amongst a plurality of tokens in the training data; and providing the trained machine learning model to enable classification of one or more instruction sequences. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: The present invention discloses a conjugate of PEG (polyethylene glycol) and rapamycin and use thereof, in particular use in preparation of a medicament for reducing immune response, wherein conjugate of PEG and rapamycin can remarkably lower the generation rate of an antibody directed to foreign immunogen, and reduce excessive immune responses caused by use thereof. The conjugate of PEG and rapamycin has beneficial effects of ensuring and even improving the treatment effect of a therapeutic agent, improving the own immunity of a subject, reducing and even eliminating graft rejection, and is advantageous in a relatively simple preparation process thereof, low cost, easy industrial production, and a high application value.

Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more scripts. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one memory. The operations may include: extracting, from an icon associated with a file, one or more features; assigning, based at least on the one or more features, the icon to one of a plurality of clusters; and generating, based at least on the cluster to which the icon is assigned, a classification for the file associated with the icon. Related methods and articles of manufacture, including computer program products, are also provided.