Abstract: This disclosure provides systems and methods for sequencing nucleic acids using nucleotide analogues and translocation of tags from incorporated nucleotide analogues through a nanopore. In aspects, this disclosure is related to composition, method, and system for sequencing a nucleic acid using tag molecules and detection of translocation through a nanopore of tags released from incorporation of the molecule.

Abstract: A method, apparatus, and non-transitory computer readable medium for data analytics are described. Embodiments of the method, apparatus, and non-transitory computer readable medium include monitoring online activity corresponding to a plurality of users; receiving aggregate marketing data for a marketing activity; identifying online activity data for a time period corresponding to the marketing activity based on the monitoring; generating a regression model based on the aggregate marketing data and the online activity data using Bayesian regression, wherein the regression model represents a relationship between the marketing activity and the online activity, comprises a time effect coefficient, and is based on a prior distribution of the time effect coefficient that decays to zero as time increases; and estimating a treatment effect for the marketing activity on the online activity based on the regression model, wherein the treatment effect comprises a rate of effect decay.

Abstract: A method and system for outage forecasting are described. One or more aspects of the method and system include receiving, by a machine learning model, time series data for a service metric of a computer network; generating, by the machine learning model, probability distribution information for the service metric based on the time series data, wherein the probability distribution information is generated using a machine learning model that is trained using a distribution loss and a classification loss; and generating, by a forecasting component, outage forecasting information for the computer network based on the probability distribution information.

Abstract: A Software Defined Network Attached Storage (SDNAS) executes on a storage system to provide access to shared file systems, referred to as “shares”, on the storage system. Users access the shares using protocol clients. To enable the SDNAS to provide differentiated prioritization between the various shares, a share priority table is maintained by the SDNAS. As shares are created, or optionally after the shares have been created, each share is assigned a share priority which is stored in the share priority table. When an IO operation is received from a protocol client on a share, the SDNAS process determines a share priority value of the share from the share priority table. The share priority value is used to specify an IO priority which used by the operating system scheduling mechanism to schedule the IO operation and to establish a CPU priority for the IO operation.

Abstract: In implementations of systems for cloud-based resource allocation using meters, a computing device implements a resource system to receive resource data describing an amount of cloud-based resources reserved for consumption by client devices during a period of time and a total amount of cloud-based resources consumed by the client devices during the period of time. The resource system determines a consumption distribution using each meter included in a set of meters. Each of the consumption distributions allocates a portion of the total amount of the cloud-based resources consumed to each client device of the client devices. A particular meter used to determine a particular consumption distribution is selected based on a Kendall Tau coefficient of the particular consumption distribution. An amount of cloud-based resources to allocate for a future period of time is estimated using the particular meter and an approximate Shapley value.

Abstract: In an embodiment, a method for performing scan includes: entering scan mode; receiving a test pattern; applying the test pattern through a first scan chain by asserting and deasserting a scan enable signal to respectively perform shift and capture operations to the first scan chain; while applying the test pattern through the first scan chain, controlling a further scan flip-flop with the first scan chain without transitioning a further scan enable input of the further scan flip-flop; and evaluating an output of the first scan chain to detect faults.

Abstract: A mobile edge computing (MEC) service area can utilize packet header source and/or destination internet protocol data and session initiation protocol source and/or destination internet protocol data to map internet protocol addresses associated with mobile devices. The MEC can comprise a translation component that translates service provider internet protocol addresses such that they are perceived as enterprise premises internet protocol addresses. Conversely, the translation component can translate enterprise premises internet protocol addresses such that they are perceived as service provider internet protocol addresses.

Abstract: In an embodiment, a method for performing scan testing includes: generating first and second scan clock signals; providing the first and second scan clock signals to first and second scan chains, respectively, where the first and second scan clock signals includes respective first shift pulses when a scan enable signal is asserted, and respective first capture pulses when the scan enable signal is deasserted, where the first shift pulse of the first and second scan clock signals correspond to a first clock pulse of a first clock signal, where the first capture pulse of the first scan clock signal corresponds to a second clock pulse of the first clock signal, and where the first capture pulse of the second scan clock signal corresponds to a first clock pulse of a second clock signal different from the first clock signal.

Abstract: A system implements a key value memory network including a key matrix with key vectors learned from training static feature data and time-series feature data, a value matrix with value vectors representing time-series trends, and an input layer to receive, for a target entity, input data comprising a concatenation of static feature data of the target entity, time-specific feature data, and time-series feature data for the target entity. The key value memory network also includes an entity-embedding layer to generate an input vector from the input data, a key-addressing layer to generate a weight vector indicating similarities between the key vectors and the input vector, a value-reading layer to compute a context vector from the weight and value vectors, and an output layer to generate predicted time-series data for a target metric of the target entity by applying a continuous activation function to the context vector and the input vector.

Abstract: This invention relates to the use of nucleoside, nucleotide and other compounds which are inhibitors or terminators of viral RNA dependent RNA polymerases or inhibitors of exonucleases as antiviral agents. These antiviral agents can be used alone or in combination with other polymerase or exonuclease inhibitors, helicase inhibitors, HCV NS5A inhibitors, HIV integrase inhibitors and HCV NS3-4A and other protease inhibitors to treat viral infections such as SARS-CoV-2, the causative agent of the COVID-19 infection.

Abstract: Disclosed herein, inter alia, are compounds, compositions, and methods of use thereof in the sequencing of a nucleic acid.

Abstract: A mobile edge computing (MEC) service area can utilized packet header source and/or destination internet protocol data and session initiation protocol source and/or destination internet protocol data to map internet protocol addresses associated with mobile devices. The MEC can comprise a translation component that translates service provider internet protocol addresses such that they are perceived as enterprise premises internet protocol addresses. Conversely, the translation component can translate enterprise premises internet protocol addresses such that they are perceived as service provider internet protocol addresses.

Abstract: A system implements a key value memory network including a key matrix with key vectors learned from training static feature data and time-series feature data, a value matrix with value vectors representing time-series trends, and an input layer to receive, for a target entity, input data comprising a concatenation of static feature data of the target entity, time-specific feature data, and time-series feature data for the target entity. The key value memory network also includes an entity-embedding layer to generate an input vector from the input data, a key-addressing layer to generate a weight vector indicating similarities between the key vectors and the input vector, a value-reading layer to compute a context vector from the weight and value vectors, and an output layer to generate predicted time-series data for a target metric of the target entity by applying a continuous activation function to the context vector and the input vector.

Abstract: Disclosed herein, inter alia, are compounds, compositions, and methods of use thereof in the sequencing a nucleic acid.

Abstract: Disclosed herein, inter alia, are compounds, compositions, and methods of use thereof in the sequencing of a nucleic acid.

Abstract: This disclosure provides systems and methods for attaching nanopore-detectable tags to nucleotides. The disclosure also provides methods for sequencing nucleic acids using the disclosed tagged nucleotides.

Abstract: This disclosure is related to a method of sequencing a single-stranded DNA using deoxynucleotide polyphosphate analogues and translocation of tags from incorporated deoxynucleotide polyphosphate analogues through a nanopore.

Abstract: Techniques for exchanging data segments between data aggregators and data consumers. In an embodiment, a value of an arbitrary data segment selected by a data consumer is computed. In particular, an individual user value is calculated for each user represented in the data segment, wherein the individual user value is a weighted sum (or other function) of the one or more features of the data segment attributable to that user, plus an additive gaussian noise. The overall value of the data segment is the sum of the individual user values. An offer price for the data segment can then be calculated using the overall value. Once a request is received from the consumer to purchase the data segment at the offer price, the data segment can be exchanged between the aggregator and consumer. Thus, a data marketplace or platform for the exchange of data segments is enabled.

Abstract: Disclosed herein, inter alfa, are compounds, compositions, and methods of use thereof in the sequencing of a nucleic acid.

Abstract: This disclosure involves predictive modeling with entity representations computed from neural network models simultaneously trained on multiple tasks. For example, a method includes a processing device performing operations including accessing input data for an entity and transforming the input data into a dense vector entity representation representing the entity. Transforming the input data includes applying, to the input data, a neural network including simultaneously trained propensity models. Each propensity model predicts a different task based on the input data. Transforming the input data also includes extracting the dense vector entity representation from a common layer of the neural network to which the propensity models are connected.