Abstract: One or more trained embedding generation artificial intelligence models are executed to generate a plurality of record attribute embeddings. The plurality of record attribute embeddings represents a plurality of attributes of data of a plurality of records. Grouping of the plurality of record attribute embeddings is performed. The grouping of a record attribute embedding includes grouping attribute values of the record attribute embedding into one or more groups of attribute values. The performing grouping provides a plurality of groups of attribute values for the plurality of record attribute embeddings. Selected records are compared to provide a set of matched records. The comparing, based on a group of attribute values, includes comparing records that include one or more attribute values grouped in the group of attribute values providing a subset of matched records of the set of matched records. The set of matched records is stored in an accessible computer location.

Abstract: A computer-implemented method includes obtaining an engineering model of a physical structure, the engineering model specifying structural elements distributed among different levels of the structure; obtaining a value of a cost metric for each of the structural elements; determining an accumulated value of the cost metric for at least one area of an architectural massing model of the structure, the at least one area being associated with a predetermined level of the different levels of the structure, the determining including calculating a direct contribution to the accumulated value of the cost metric, and calculating an indirect contribution to the accumulated value of the cost metric; and displaying the accumulated value of the cost metric for the at least one area of the architectural massing model of the structure.

Abstract: A computer-implemented method, system and computer program product for performing semantic matching in a data fabric. Knowledge graphs are populated with metadata enriched with master data. Based on such knowledge graphs with the metadata enriched with the master data, a trained multi-layer graph neural network generates embeddings. Furthermore, behavioral metadata from data stewards are monitored and collected. Such behavioral metadata may be used to enrich metadata, which are populated in knowledge graphs which are inputted into the multi-layer graph neural network to generate embeddings. Upon generating the embeddings discussed above, semantic matching of the data assets in the data fabric using the embeddings is performed. In this manner, semantic matching of the data assets in the data fabric is more effectively performed by utilizing master data and behavioral metadata.

Abstract: Records can be matched by a graph neural network model performing entity resolution on the records, and representing each record as a respective node in a graph. Record matching explanations can be generated, each record matching explanation indicating a first set of attributes, and a first set of corresponding values, used for the matching at least two of the records. Nodes can be clustered into a plurality of clusters by aggregating the record matching explanations and, based on the record matching explanations, determining which of the records have high importance values, in the first set of values, that match. At least one cluster explanation can be generated, the cluster explanation indicating a second set of attributes, and a second set of values corresponding to the second set of attributes, used for the clustering the nodes. The record matching explanation and the cluster explanation can be output.

Abstract: A computer implemented method classifies records. A number of processor units creates a training dataset comprising subgraphs of matched records matched to an entity and identifying an importance of attributes in the matched records. The matched records in a subgraph are related to each other by a subset of the attributes. The number of processor units trains a graph neural network using the training dataset. The graph neural network classifies the records as belonging to the entity.

Abstract: There is provided a compound represented by general formula (Ib), wherein ring A is a carbocyclic or heterocyclic ring, a reaction product of the reaction between one or more said compounds and one or more amine containing compounds. Also provided is related production methods thereof.

Abstract: There is provided a method of crosslinking a polyhydroxyurethane (PHU) polymer having a plurality of diene moieties, preferably furan in the backbone and a crosslinked PHU polymer by reacting with a crosslinking agent having two or more dienophile moieties. Also provided is a method of removing the crosslinks of a crosslinked PHU polymer comprising a plurality of diene-dienophile adducts.

Abstract: Records can be matched by a graph neural network model performing entity resolution on the records, and representing each record as a respective node in a graph. Record matching explanations can be generated, each record matching explanation indicating a first set of attributes, and a first set of corresponding values, used for the matching at least two of the records. Nodes can be clustered into a plurality of clusters by aggregating the record matching explanations and, based on the record matching explanations, determining which of the records have high importance values, in the first set of values, that match. At least one cluster explanation can be generated, the cluster explanation indicating a second set of attributes, and a second set of values corresponding to the second set of attributes, used for the clustering the nodes. The record matching explanation and the cluster explanation can be output.

Abstract: According to a first aspect there is disclosed an assembly comprising a power device and a cooling plate which overlies the power device for heat transfer therebetween. The power device comprises a plurality of power switching components including at least a first power switching component and a second power switching component; wherein each of the power switching components is configured to dissipate heat to the cooling plate.

Abstract: Described herein are systems and methods of for conducting various biological assays on arrays utilizing electrowetting on dielectric (EWOD). The systems and methods may process the biological sample, or plurality thereof, using at least one droplet. The droplet, or plurality thereof, may be manipulated using the systems and methods described herein. Further described herein are improvements to arrays for facilitating the execution of biological assays on the arrays.

Abstract: One or more computing devices, systems, and/or methods are provided. Event information associated with a plurality of events may be identified. The plurality of events may be associated with first entities corresponding to a first entity type and second entities associated with a second entity type. A first network profile associated with the first entities and the second entities may be generated based upon the event information. An iterative process may be performed to identify a coalition network associated with fraudulent activity. The iterative process may include analyzing the first network profile to identify a first set of entities, of the first entities, that are related to an entity of the second entities, and/or analyzing the first network profile to identify a second set of entities, of the second entities, that are related to the first set of entities. Multiple iterations may be performed to identify the coalition network.

Abstract: There is provided a polymer or derivative thereof comprising a plurality of active amine groups in the backbone, wherein the polymer is a reaction product of a reaction between one or more bis-carbonates and one or more amine compounds having at least two terminal amino groups. Also provided are use of the polymer or derivative thereof and a method of preparing the polymer or derivative thereof.

Abstract: Compositions, kits and methods for detecting a plurality of targets are provided herein. A probe-set composition is provided, including one or more first probes and one or more second probes. Each of the first probe includes a nucleic acid sequence complementary to a nucleic acid barcode of a corresponding target-specific binding partner, a first label, and a cleavage site for a first cleavage agent, wherein the first cleavage agent is capable of releasing the first label. Each of the second probes includes a nucleic acid sequence complementary to a nucleic acid barcode of a corresponding target-specific binding partner, a second label, a quench moiety that renders the second label undetectable, and a cleavage site for the first cleavage agent. The first cleavage agent is capable of releasing the quench moiety, whereby the second label is rendered detectable.

Abstract: Described are conjugates of nucleic acid nanotubes and cells by linking the nanotubes to a cell surface moiety. Devices, kits, systems, and methods comprising the nanotube cell conjugates are also described.

Abstract: Systems and methods detect a potential hacking attack by monitoring the number and timing of DELBA (Delete Block Acknowledgement) action frames. When the number and timing of the DELBA action frames correspond to an unauthorized access pattern, an unauthorized access is detected. The potential unauthorized access may be detected by an access point (AP) or by the AP and a backend system. When a potential unauthorized access is detected, the AP may remain in silent mode for a longer period of time and limit access to the network to only trusted devices. In addition, an alarm or other notification of the potential unauthorized access may be provided to a user or other designated contact.

Abstract: Compositions, kits and methods for detecting a plurality of targets are provided herein. A probe-set composition is provided, including one or more first probes and one or more second probes. Each of the first probe includes a nucleic acid sequence complementary to a nucleic acid barcode of a corresponding target-specific binding partner, a first label, and a cleavage site for a first cleavage agent, wherein the first cleavage agent is capable of releasing the first label. Each of the second probes includes a nucleic acid sequence complementary to a nucleic acid barcode of a corresponding target-specific binding partner, a second label, a quench moiety that renders the second label undetectable, and a cleavage site for the first cleavage agent. The first cleavage agent is capable of releasing the quench moiety, whereby the second label is rendered detectable.

Abstract: One or more computing devices, systems, and/or methods are provided. Event information associated with a plurality of events may be identified. The plurality of events may be associated with first entities corresponding to a first entity type and second entities associated with a second entity type. A first network profile associated with the first entities and the second entities may be generated based upon the event information. An iterative process may be performed to identify a coalition network associated with fraudulent activity. The iterative process may include analyzing the first network profile to identify a first set of entities, of the first entities, that are related to an entity of the second entities, and/or analyzing the first network profile to identify a second set of entities, of the second entities, that are related to the first set of entities. Multiple iterations may be performed to identify the coalition network.

Abstract: One or more computing devices, systems, and/or methods are provided. First event information associated with a plurality of events may be determined, wherein the plurality of events is associated with a first entity. A set of event metrics associated with the first entity may be determined based upon the first event information. A first combined metric may be determined based upon at least two metrics of the set of event metrics. Whether the first entity is fraudulent may be determined based upon the first combined metric and a threshold metric associated with anomalous behavior.

Abstract: A method and apparatus for pre-processing a photoplethysmogram (PPG) signal include receiving, by an apparatus, the PPG signal including a plurality of pulses, obtaining, by the apparatus, a smoothed PPG signal based on smoothing the PPG signal using a moving average filter, obtaining, by the apparatus, a drift removed PPG signal based on removing drift from the smoothed PPG signal using a fitted polynomial function, and obtaining, by the apparatus, a rectified PPG signal based on correcting a motion artifact of the drift removed PPG signal by replacing each of the plurality of pulses using a combination of a global signal pulse and a corresponding local signal pulse.

Abstract: The present disclosure relates to a method and system for processing a photoplethysmogram (PPG) signal to improve accuracy of measurement of physiological parameters of a subject. The method may include removing a baseline drift from the PPG signal; obtaining a drift removed signal; filtering the drift removed signal; obtaining a filtered signal; performing motion artifact correction on the filtered signal; and obtaining a corrected signal.