Abstract: A method and apparatus for performing search system upgrades is described. The method may include processing a software upgrade for a search system cluster distributed over one or more nodes, the one or more nodes comprising current search system data nodes. The method may also include allocating at least a set of one or more search system data nodes for the software upgrade including at least one upgraded search system data node. Furthermore, the method can include receiving, during the software upgrade, transaction data for a transaction, and receiving search requests to be executed by the search system cluster.

Abstract: The present disclosure provides a robust and effective solution to an entity or an organization by enabling the entity to implement a system for 3D vision, and synthetic data generation of a retail product model. Further, the present disclosure aims at generating high-quality, photorealistic, large-scale domain-specific synthetic data. The system is equipped with synthetic simulation, digital twin creation, and synthetic data generation with automated annotations. Additionally, the system allows the training of artificial intelligence to reduce manual efforts and to facilitate the automation and personalization.

Abstract: According to one embodiment, a method, computer system, and computer program product for anomaly detection is provided. The embodiment may include receiving login event data of a customer. The embodiment may include labeling each login request of the event data as non-anomalous or anomalous. The embodiment may include performing aggregate feature extraction for each login request. The embodiment may include filtering data of anomalous login requests from data of non-anomalous login requests. The embodiment may include training an autoencoder machine learning model using the data of non-anomalous login requests to learn non-anomalous login request behavior. The embodiment may include passing the data of anomalous login requests through the trained autoencoder ML model to obtain enriched data. The embodiment may include training a classifier model using the enriched data to identify anomalous login requests and output a classification with confidence value.

Abstract: The method performs at the orchestration interface at which update information, including changes to tasks of a workflow, is received from a task manager system (TMS), where the workflow includes a set of tasks, inputs to the tasks, and outputs from the tasks. The inputs and outputs determine runtime dependencies between the tasks. Based on the update information received, the orchestration interface populates a topology of nodes and edges as a directed acyclic graph (DAG) that maps nodes to tasks and edges to runtime dependencies between tasks, based on node inputs and outputs. The orchestration interface instructs the execution of the tasks and handling dependencies by interacting with a task execution system (TES) and by traversing the DAG, the orchestration interface identifies tasks that depend on completed tasks as per the runtime dependencies and instructs the TES to execute the dependent tasks identified.

Abstract: Apparatus, systems, articles of manufacture, and methods for improving anti-malware scan responsiveness and effectiveness using user symptoms feedback are disclosed. An example method includes detecting a performance issue on a computing device, presenting a user interface on a display of the computing device requesting user feedback regarding the performance issue, and synthesizing user input related to the performance issue to identify, on the computing device, a scan parameter associated with the performance issue. The example method further includes, in response to failing to identify the scan parameter on the computing device, transmitting the user input to a symptom analysis server to identify the scan parameter based on anti-malware scans from other computing devices, and, in response to determining the scan parameter, performing a targeted anti-malware scan on the computing device.

Abstract: Systems, apparatuses and methods may provide for technology that parses, at runtime, a deep learning graph in topological order to identify a plurality of nodes, marks a first set of nodes in the plurality of nodes as unsupported by target hardware, and marks a second set of nodes in the plurality of nodes as supported by the target hardware, wherein the first set of nodes and the second set of nodes are marked based on one or more attributes defining operation functionality, and wherein the one or more attributes include one or more of an input node parameter, a dimension, or a shape.

Abstract: A system, method and device for enhanced authentication of network elements are provided. The device may be configured to: obtain device information from a network element, transmit the obtained device information to a storage device in order to determine whether the network element supports authentication in accordance with a first authentication protocol, based on determining that the network element supports the authentication in accordance with the first authentication protocol, facilitate authentication of the network element with a first authentication server configured to perform the authentication in accordance with the first authentication protocol, and based on determining that the network element does not support the authentication in accordance with the first authentication protocol, facilitate the authentication of the network element with at least one server configured to perform authentication in accordance with a second authentication protocol.

Abstract: A method and apparatus for verifying integrity of search system data is described. The method may include accessing a first and second snapshot of search system data, the search system data in each snapshot including transaction data generated by a commerce platform system in response to transactions performed by the commerce platform system. The method may also include accessing an operation log of operations performed on the transaction data during a time between when the first snapshot was generated and a time when the second snapshot was generated. Furthermore, the method may include transforming the transaction data from the first snapshot based on the operations in the operation log to generate validated transaction data in a validated second snapshot, and determining a reliability of the transaction data at the second time period based on a comparison of transaction data from the second snapshot with the validated transaction data from the validated second snapshot.

Abstract: The present disclosure is concerned with purine diamine compounds for the treatment of conditions associated with BRD4, RIP3K, and/or IL6 signaling dysfunction such as, for example, cancer (e.g., lung cancer, skin cancer, bladder cancer, kidney cancer, liver cancer), arsenicosis, arsenic poisoning, inflammation, skin lesions, dysfunction of systemic organs, and skin blisters. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present invention.

Abstract: Targeted acquisition of data for model training includes identifying attributes of classified samples of a collection of samples classified by a classification model, and generating at least one query based on the identified attributes, the at least one query tailored, based on the attributes, to retrieve additional training data for training the classification model to more accurately classify samples and avoid incorrect sample classification.

Abstract: Provided herein, inter alia, are compositions comprising one or more biologically pure strains of bacteria as well as methods of making and using the same to treat and/or prevent one or more obesity related disorders in a subject in need thereof.

Abstract: A system and method provide for automated management of policies in an application platform. A plurality of policy groups are established, each according to a set of included policies and a set of assigned application groups, where each policy defines a requirement and an automated response, and each application group is defined according to a rule to determine whether an application is contained within. A configuration file for each policy group associates each assigned application group with each included policy. An automatic configuration, according to the configuration file for each of the policy groups, configures an admission controller of the application platform to selectively test an application contained within an application group and designated for deployment to the application platform, to determine whether it meets the requirement of each policy associated with the application group, and to selectively execute the automated response based on a failure to fulfill the requirement.

Abstract: Disclosed herein are system, method, and computer program product embodiments for converting queries and scripts used in big data systems. A script conversion system converts a script and its queries from a first big data format to a second big data format. The script conversion system uses a configuration mapping that includes direct and/or indirect function mappings. For the direct mapping, the script conversion system replaces the function with a new function in the second big data format. For the indirect mapping, the script conversion system constructs an equivalent function in the second big data format using information extracted from parsing queries in the first big data format. The script conversion system also formats a converted query using a project mapping and/or generates a conversion report indicating successful or unsuccessful conversions. Scripts may be converted from an on-premises data warehouse system to a cloud-based data warehouse system.

Abstract: The present disclosure is drawn to cleansing compositions. The cleansing compositions include: (a) one or more anionic surfactants; (b) one or more nonionic emulsifiers having a Hydrophile-Lipophile Balance (HLB) of about 6 or less; (c) one or more salts providing divalent cations having a charge density of about 40 to about 200 C/mm3 and a water solubility of at least 400 g/L; (d) one or more anionic polymers; (e) one or more water soluble solvents; and (f) water. The cleansing compositions have a unique lamellar liquid crystal structure and are useful in methods for cleansing the body, including the skin and hair.

Abstract: An input/output module (IOM) for use within a network storage system mounted within a rack enclosure. The IOM includes a switching component configured to provide top-of-rack (TOR) switching for data to be routed from input connectors to data storage devices within the rack enclosure. The IOM also includes a protocol interface configured to convert a protocol of the data from an input data protocol (e.g., Ethernet, Fibre Channel or InfiniBand™) to a protocol for use with the storage devices (e.g., nonvolatile memory express (NVMe) and Peripheral Component Interconnect Express (PCIe)). Among other features, the IOM allows switching to be dis-aggregated from a TOR switch and distributed throughout the data network of the rack.

Abstract: Provided herein, inter alia, are methods for improving the growth of cells (such as probiotic cells or recombinant cells) by culturing the cells in a liquid media comprising one or more enzymes that hydrolyze at least one nucleoside triphosphate present in the media. Cells cultured in accordance with these methods exhibit improved growth compared to cells cultured in media that does not comprise one or more enzymes that hydrolyze at least one nucleoside triphosphate.

Abstract: To configure an application platform for policy-based automated exception handling, a plurality of policies are established, each defining a requirement for applications. A plurality of exceptions are also established, each defining an expiration time and indicating at least one of the policies. A processor automatically generates a configuration file associating each of the exceptions with each policy indicated in the exception. The processor then automatically configures the application platform according to the configuration file. As a result of this configuration, an admission controller of the platform selectively tests an application designated for deployment to the application platform, based on a determination whether an exception assigned to the application is presently applicable to the policy. The exception is presently applicable based on an association of the exception with the policy in the configuration file, and a comparison of a present time with the exception's expiration time.

Abstract: A method, computer system, and a computer program product for classification training are provided. A deep learning model is trained with a first dataset that includes annotated samples that include a first and second class. Last hidden state features corresponding to respective tokens from prototypes of the first and second class are saved. The trained deep learning model is further trained with a second dataset that includes additional annotated samples that include the first and second class and a third class. The further training includes performing a cosine similarity loss optimization and a cross entropy loss optimization. The cosine similarity loss optimization is of last hidden state features resulting from the further trained deep learning model and the first class and the second class compared to the saved last hidden state features. The cross entropy loss optimization is for classification of the first, second, and the third class.

Abstract: The present invention relates to compounds of formula (I). The compounds may be used to antagonise the Stimulator of Interferon Genes (STING) protein and may thereby treat liver fibrosis, fatty liver disease, non-alcoholic steatohepatitis (NASH), pulmonary fibrosis, lupus, sepsis, rheumatoid arthritis (RA), type I diabetes, STING-associated vasculopathy with onset in infancy (SAVI), Aicardi-Goutieres syndrome (AGS), familial chilblain lupus (FCL), systemic lupus erythematosus (SLE), retinal vasculopathy, neuroinflammation, systemic inflammatory response syndrome, pancreatitis, cardiovascular disease, renal fibrosis, stroke and age-related macular degeneration (AMD).

Abstract: An input/output module (IOM) for use within a network storage system mounted within a rack enclosure. The IOM includes a switching component configured to provide top-of-rack (TOR) switching for data to be routed from input connectors to data storage devices within the rack enclosure. The IOM also includes a protocol interface configured to convert a protocol of the data from an input data protocol (e.g., Ethernet, Fibre Channel or InfiniBand™) to a protocol for use with the storage devices (e.g., nonvolatile memory express (NVMe) and Peripheral Component Interconnect Express (PCIe)). Among other features, the IOM allows switching to be dis-aggregated from a TOR switch and distributed throughout the data network of the rack.