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: A content addressable memory (CAM) device includes multiple CAM sub-banks Each CAM sub-bank includes an array of CAM cells arranged in rows and columns and partitioned into a first stage and a second stage along a column dimension. Each CAM sub-bank further includes first-stage match lines (MLs), first-stage search line (SL) pairs, second-stage MLs, and second-stage SL pairs. Each second-stage SL pair is coupled to a column of CAM cells in the second stage and is gated by an SL enable (SL_EN signal). Each CAM sub-bank further includes a circuit operative to receive all of the first-stage MLs as input and de-assert the SL_EN signal when none of the first-stage MLs indicate a match. De-assertion of the SL_EN signal blocks a second portion search key from being provided to the second-stage SL pairs.

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 and methods for treating and/or preventing conditions associated with gut inflammation caused by dysbiosis via use of exogenously administered acid phosphatases or enzymes of the GDA1_CD39 superfamily (such as apyrases).

Abstract: A method, performed by at least one processor of a trust broker, for establishing trust of vendor-supplied Open Radio Access Network (O-RAN) software, includes: receiving a plurality of O-RAN software from a plurality of O-RAN software vendors, the plurality of O-RAN software respectively signed by the plurality of O-RAN software vendors; for a software, among the plurality of O-RAN software, verifying a signature included with the software using a vendor certificate issued by a certificate authority (CA) of the corresponding vendor; based on successful verification of the signature, performing a software attestation with respect to the software using a digital certificate issued by a CA of the trust broker; and providing the attested software to an operator corresponding to the O-RAN system and with which the trust broker has a trust relationship.

Abstract: Memory calibration with a margin check is disclosed. A memory subsystem includes a memory and a memory controller coupled to the memory. The memory controller includes a calibration circuit configured to perform, during an initialization process, horizontal memory calibrations for ones of a plurality of performance states and to determine and store, in a storage circuit, information indicative of a set of differences between calibration results for pairs of the plurality of performance states. The memory controller is further configured to, subsequent to the initialization process and in response to a change from a first one of the plurality of performance states to a second one of the plurality of performance states set initial memory parameters for the second performance state based on the set of differences. Thereafter, operation begins in the second performance state without performing an initial horizontal calibration.

Abstract: Targeted acquisition of data for model training includes automatically generating metadata describing samples, of an initial dataset, in neighborhoods of an embedding space in which the samples are embedded. The samples described by the automatically generated metadata are classified by a classification model, and include both correctly classified samples in the neighborhoods and incorrectly classified samples in the neighborhoods. Additionally, attributes of one or more correctly classified samples of the collection of samples and one or more incorrectly classified samples of the collection of samples are identified, and queries are generated based on the identified attributes, the queries 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: Methods, apparatus, systems and articles of manufacture are disclosed to improve anti-malware scan responsiveness, in response to a performance issue on a user computing device, determine a symptom associated with the performance issue based on a user input from the user computing device, the user input corresponding to highlighting an area of a display associated with the performance issue, a window having been rendered on the display by an operating system of the user computing device, identify a scan parameter for a targeted anti-malware scan based on positive results of malware scans from other user computing devices that experienced the symptom, and transmit the scan parameter to the user computing device to facilitate a targeted anti-malware scan of the user computing device based on the scan parameter.

Abstract: A system includes one or more source memory devices of a source computing environment that store a database comprising data files, wherein each of a plurality of data tables of the source computing environment includes data from one or more of the data files, one or more target memory devices of a target computing environment and at least one processor configured to receive a command to copy data files from the source memory devices to the target memory devices, detect that the target memory devices have insufficient memory, calculate a value coefficient for each data table, assign a priority index to each data table based on the value coefficient, order the data files in a copy queue based on the priority index of the data tables, and copy the ordered data files to the target memory devices.

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: A system includes one or more source memory devices of a source computing environment that store a database comprising data files grouped in a plurality of file groups, wherein each of a plurality of data tables of the source computing environment includes data from one or more of the data files grouped in to one or more of the file groups, one or more target memory devices of a target computing environment and at least one processor configured to receive a command to copy data files from the source memory devices to the target memory devices, detect that the target memory devices have insufficient memory, calculate a value coefficient for each data table, assign a priority index to each data table based on the value coefficient, re-arrange the file groups based on priority indices of the data tables, and copy the re-arranged file groups to the target memory devices.

Abstract: A system includes one or more source memory devices of a source computing environment that store a database comprising data files grouped in a plurality of file groups, wherein each of a plurality of data tables of the source computing environment includes data from one or more of the data files grouped in to one or more of the file groups, one or more target memory devices of a target computing environment and at least one processor configured to receive a command to copy data files from the source memory devices to the target memory devices, detect that the target memory devices have insufficient memory, calculate a value coefficient for each data table, assign a priority index to each data table based on the value coefficient, re-arrange the file groups based on priority indices of the data tables, and copy the re-arranged file groups to the target memory devices.

Abstract: A method, computer system, and a computer program product for data pipeline prioritization is provided. Embodiments may include receiving, by a cognitive rules engine, one or more data pipelines. Embodiments may then include analyzing, using a computational method of the cognitive rules engine, the one or more data pipelines. Embodiments may lastly include prioritizing the one or more data pipelines based on a result of the computational method of the cognitive rules engine.

Abstract: A computer-implemented method generates an automated data movement workflow. The method includes transforming a received request for data, which was received in a restricted natural language form, into a form suitable for accessing a metadata repository. The method further includes identifying data and data dependencies using the transformed request for data. The method further includes building a workflow using the identified data and data dependencies. The method further includes, upon applying at least one governance rule to the workflow, modifying the built workflow to be compliant with the at least one governance rule, and if no compliance with the at least one governance rule is achievable, recommending a change to the built workflow.

Abstract: Embodiments for identifying an optimal cloud computing environment for a computing task is disclosed. Embodiments comprises receiving a computing task to be executed in a cloud computing environment, wherein the computing task requires a set of cloud computing environment parameter values of the cloud computing environment, pre-selecting a set of candidate cloud computing environments, each of which meets the set of cloud computing environment parameter values, ranking the candidate cloud computing environments using reward-based ranking parameter values of the candidate cloud computing environments as an additional selection constraint, and selecting the highest ranking cloud computing environment as the optimal cloud computing environment for the computing task.

Abstract: One or more systems and/or methods for product similarity detection and recommendation are provided. Users may view articles and/or other content that includes images depicting products that may be of interest to the users. These images are processed using image processing functionality such as computer vision to identify the products depicted by the images. A vector embedding model is used to generate product vector representations of the products. Catalog items that are available from a catalog to supplement the articles and other content may be processed to generate catalog item vector representations. When content (an article) with an image depicting a product is to be displayed to the user, similarity between a product vector representation of the product and the catalog item vector representations is determined in order to identify and display catalog items depicting products that are similar to the product depicted by the image in the content.

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: 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 m need thereof.

Abstract: An approach is provided for completing a pipeline graph. Using a deep learning based sequence model, an initial data pipeline having a sequence of nodes is generated. Mismatch(es) between data formats required by input and output in the sequence of nodes is identified. Virtual gap node(s) that correct the mismatch(es) are added to the initial data pipeline. For a given virtual gap node, tentative graph structures are determined using knowledge graphs and a crowd sourced validation system. Reuse forecast scores and performance scores for the tentative graph structures are calculated. Based on the reuse forecast scores and the performance scores, a final graph structure for implementing the given virtual gap node is determined.

Abstract: A system includes one or more source memory devices of a source computing environment that store a database comprising data files grouped in a plurality of file groups, wherein each of a plurality of data tables of the source computing environment includes data from one or more of the data files grouped into one or more of the file groups, one or more target memory devices of a target computing environment and at least one processor configured to calculate a number of read operations per megabyte (MB) for a data table, a number of write operations per MB, obtain an importance index of the table, weight the reads per MB, writes per MB and the importance index by respective user-defined weights, determine a criticality index of the table, calculate a value coefficient of the table, and assign a data file based on the value coefficient of the table.