Abstract: A labeling function associated with generating one or more semantic concepts is received. The received labeling function is used to automatically annotate an existing dataset with the one or more semantic concepts to generate an annotated noisy dataset. A reference dataset annotated with the one or more semantic concepts is received. A training dataset is prepared including by combining at least a portion of the reference dataset with at least a portion of the annotated noisy dataset. The training dataset is used to train a multi-task machine learning model configured to perform both a decision task to predict a decision result and an explanation task to predict a plurality of semantic concepts for explainability associated with the decision task.

Abstract: The present invention belongs to the field of household appliances, more particularly to the field of household appliances for storing and sifting tapioca gum so that this gum reaches adequate grain size for the preparation, through mechanical processes as granulation through pressure or extrusion. The invention also brings the advantage of avoiding manual contact with the gum, allowing all the processing of the gum to happen inside a container, as for example a cup, avoiding the entrance of dirt and contaminants, as well as distributing it in a directed way, avoiding the sifted or extruded gum to be spilled out of the frying pan.

Abstract: Generating employee retention insights is provided. An analysis is performed, using an artificial intelligence component, of data in a completed digital off-boarding form corresponding to a particular employer and a type of a particular employee leaving the particular employer and information in data feeds from a plurality of different data sources. Insights are generated, using the artificial intelligence component, into employee retention for the type of the particular employee corresponding to the particular employer based on the analysis of the data in the completed digital off-boarding form and the information in the data feeds from the plurality of different data sources. A set of action steps are generated, using the artificial intelligence component, based on the insights and the data in the completed digital off-boarding form. One or more of the set of action steps are performed automatically.

Abstract: Pharmaceutical formulations with a tropomyosin-related kinase inhibitor (“Trk inhibitor”) are disclosed. The pharmaceutical formulations comprise 3-(3-methoxy-4-((4-methoxybenzyl)oxy)benzyl)-6-(1-methyl-1H-pyrazol-4-yl)-3H-imidazo[4,5-b]pyridin-2-amine in microcrystalline suspension formulations in its monohydrate form, which shows improved characteristics over the anhydrate form, and in extended release formulations. The extended release pharmaceutical formulations comprise 3-(3-methoxy-4-((4-methoxybenzyl)oxy)benzyl)-6-(1-methyl-1H-pyrazol-4-yl)-3H-imidazo[4,5-b]pyridin-2-amine-loaded microspheres.

Abstract: A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) ?1, ?2, . . . , ?n forming a second set of evidences U. A subset of concept graphs of nodes is selected from c?1, c?2, . . . , c?n according to a computable measure of consistency, inconsistency and/or priority threshold between c?j in c?1, c?2, . . . , c?n to specification concept graph speck in spec1, spec2, . . . , specm. Knowledge fragments are generated for corresponding subset of concept graphs c?i1, c?i2, . . .

Abstract: The present invention relates to an analytical method that includes providing a sample potentially containing a chiral analyte that can exist in stereoisomeric forms, and providing a probe selected from the group consisting of metal salts. The sample is contacted with the probe under conditions that permit coordination of the probe to the analyte, if present in the sample; and, based on any coordination that occurs, the absolute configuration of the analyte in the sample, and/or the concentration of the analyte in the sample, and/or the enantiomeric composition of the analyte in the sample is/are determined.

Abstract: A multi-task hierarchical machine learning model is configured to perform both a decision task to predict a decision result and an explanation task to predict a plurality of semantic concepts for explainability associated with the decision task, wherein a semantic layer of the machine learning model associated with the explanation task is utilized as an input to a subsequent decision layer of the machine learning model associated with the decision task. Training data is received. The multi-task hierarchical machine learning model is trained using the received training data.

Abstract: Systems and methods for limiting facilitating a multi-modal transportation itinerary are provided. The system includes a service entity computing system and a vehicle provider computing system that collaborate to create and facilitate an end-to-end multi-modal transportation itinerary. This can include creating a flight schedule during a time window based on multi-modal transportation service data supplied by the service entity. The service entity can generate multi-modal transportation itineraries based on a request and the flight schedule. A rider can select an itinerary and, in response, the service entity can initiate and monitor a first ground leg of the itinerary. Deviations from the first ground leg can be provided to the vehicle provider which can delay or advance a flight based on the deviation. Likewise, deviations from an aerial transportation leg can be provided to the service entity which can delay or advance a second ground leg based on the deviation.

Abstract: A series of sequential inputs and a prediction output of a machine learning model, to be analyzed for interpreting the prediction output, are received. An input included in the series of sequential inputs is selected to be analyzed for relevance in producing the prediction output. Background data for the selected input of the series of sequential inputs to be analyzed is determined. The background data is used as a replacement for the selected input of the series of sequential inputs to determine a plurality of perturbed prediction outputs of the machine learning model. A relevance metric is determined for the selected input based at least in part on the plurality of perturbed prediction outputs of the machine learning model.

Abstract: Aspects of the present disclosure are directed to creating and administering artificial reality collaborative working environments and providing interaction modes for them. An XR work system can provide and control such artificial reality collaborative working environments to enable, for example, A) links between real-world surfaces and XR surfaces; B) links between multiple real-world areas to XR areas with dedicated functionality; C) maintaining access, while inside the artificial reality working environment, to real-world work tools such as the user's computer screen and keyboard; D) various hand and controller modes for different interaction and collaboration modalities; E) use-based, multi-desk collaborative room configurations; and F) context-based auto population of users and content items into the artificial reality working environment.

Abstract: The present invention relates to the detection of malicious software in electronic documents and comprises: detecting an executable code in the electronic document provided to a client module; extracting information from the electronic document comprising the executable code and metadata of the electronic document; creating a binary vector associated with the electronic document; comparing, in a classifier module (200), the binary vector with one or more groups of vectors previously classified and stored in a database (400); classifying the vector in one of the groups, where each group has associated therewith a verdict about the presence of malicious software; and determining that the document contains malicious software depending on the verdict associated with the group in which its associated vector has been classified.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting future adverse health events using neural networks. One of the methods includes receiving electronic health record data for a patient; generating, from the electronic health record data, an input sequence comprising a respective feature representation at each of a plurality of time window time steps, comprising, for each time window time step: determining, for each of the possible numerical features, whether the numerical feature occurred during the time window; and generating, for each of the possible numerical features, one or more presence features that identify whether the numerical feature occurred during the time window; and processing the input sequence using a neural network to generate a neural network output that characterizes a predicted likelihood that an adverse health event will occur to the patient.

Abstract: A measurement system includes a motion capture system comprising at least one motion capture device configured to detect the motion of one or more body portions of a system user and generate output data; a sensory output device, the sensory output device configured to generate sensory feedback for delivery to the system user; and at least one data processing device operatively coupled to the motion capture system and the sensory output device, the at least one data processing device further configured to determine, by utilizing a trained neural network, one or more poses and/or movements of the one or more body portions of the system user from the motion capture output data, and to provide sensory feedback to the system user, by means of the sensory output device, as to conformity of the one or more poses and/or movements to one or more reference poses and/or movements.

Abstract: Described herein is a computer implemented method. The method comprises detecting user input activating a text effect selection control. In response to the first user input the method further comprises: automatically generating and displaying a first shadow for a selected design element, the first shadow having a first colour, a first offset value, and a first direction; and automatically generating and displaying a second shadow for the selected design element, the second shadow having a second colour, the first offset value, and a second direction, the second direction being opposite the first direction.

Abstract: This invention concerns a method for preparing a bacterial supernatant comprising culturing a cell of Pseudomonas environmental strain PF-11; and recovering the supernatant. This invention also concerns a method for reducing the amount of a biofilm on a surface, reducing adhesion of at least one organism to a surface, or reducing microfouling or macrofouling on a surface comprising contacting the surface with a supernatant, supernatant fraction, modified supernatant or modified supernatant fraction of Pseudomonas strain PF-11; or a composition comprising a supernatant, supernatant fraction, modified supernatant or modified supernatant fraction of Pseudomonas strain PF-11, and one or more acceptable carriers.

Abstract: Systems and methods for lossless compression of tabular numeric data are provided. The system can include one or more data compression servers executing data compression system code to compress the tabular numeric data, a storage database to store the compressed tabular numeric data, and one or more data decompression servers to decompress the tabular numeric data for use. The one or more data compression servers, the storage database, and the one or more data decompression servers can communicate via a communication network. The system can receive the uncompressed tabular numeric data from one or more data generation systems, processes the uncompressed tabular numeric data with the data compression system code, and generate a compressed table of numeric information, which can be stored in the database, or later decompressed by the one or more data decompression servers.

Abstract: Disclosed is a railroad switch device for moving railroad switch points. The device includes two spring assembly sets placed over two switch operation rods. The spring assembly sets move railroad switch points and keep railroad switch points against a stock rail. At least one sensor is mounted adjacent to two switch operation rods. The switch operation rods have a switch point position target connected to the switch operation rods. The switch point position target follows a movement of two throw rods. The two spring assembly sets provide a spring holding force to the two switch operation rods. The spring holding force provides a safe operation of a switch point position assembly by at least one of determining that the spring holding force is present in the moving railroad switch point, and pushing the spring holding force towards the switch point position assembly away from the at least one sensor.