Abstract: A system for operating a cross-vertical service comprises a processor and memory storing instructions that cause the processor to effectuate operations. The operations include receiving, at the cross-vertical service, a registration of a first device from a first vertical service associated with the first device and registering the cross-vertical service with a second vertical service. The operations include retrieving data from the second vertical service and monitoring a characteristic of the first device. The operations include, based on at least one of the data and the characteristic, communicating a trigger to the second vertical service to effect an action. In response to the trigger, the second vertical service performs the action.

Abstract: Aspects of the subject disclosure may include, for example, a method in which first performance data and second performance data are obtained for a first virtual machine and a second virtual machine on a network, the performance data is analyzed, performance of the first virtual machine is predicted, and a performance trend for the first virtual machine is determined. Performance of the second virtual machine is predicted in accordance with analyzing of the second performance data and a potential transfer of execution of an application from the first virtual machine to the second virtual machine. Execution of the application is transferred to the second virtual machine after determining an expected improvement in execution of the application relative to the first virtual machine. Other embodiments are disclosed.

Abstract: This invention provides methods of using labeled nucleotide polyphosphate analogues to detect the identity or presence of a nucleotide at certain positions in nucleic acid sequences with single molecule sensitivity using nanopore detection, nucleotides and primer-conjugated nanopore proteins for use in such methods, and processes for producing such nucleotides and primer-conjugated nanopore proteins.

Abstract: This invention provides nucleoside polyphosphate analogs each of which comprises a tag comprising a plurality of Raman-scattering moieties; compounds comprising said nucleoside polyphosphate analogs; and methods for determining the sequence of a single-stranded DNA or RNA using said nucleoside polyphosphate analogs. This invention also provides methods for detecting the interaction of a plurality of predetermined compounds, at least one of which having attached thereto a tag comprising a plurality of Raman-scattering moieties.

Abstract: Certain embodiments involve extracting seasonal, level, and spike components from a time series of metrics data, which describe interactions with an online service over a time period. For example, an analytical system decomposes the time series into latent components that include a seasonal component series, a level component series, a spike component series, and an error component series. The decomposition involves configuring an optimization algorithm with a constraint indicating that the time series is a sum of these latent components. The decomposition also involves executing the optimization algorithm to minimize an objective function subject to the constraint and identifying, from the executed optimization algorithm, the seasonal component series, the level component series, the spike component series, and the error component series that minimize the objective function. The analytical system outputs at least some latent components for anomaly-detection or data-forecasting.

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: Aspects of the subject disclosure may include, for example, a method in which first performance data and second performance data are obtained for a first virtual machine and a second virtual machine on a network, the performance data is analyzed, performance of the first virtual machine is predicted, and a performance trend for the first virtual machine is determined. Performance of the second virtual machine is predicted in accordance with analyzing of the second performance data and a potential transfer of execution of an application from the first virtual machine to the second virtual machine. Execution of the application is transferred to the second virtual machine after determining an expected improvement in execution of the application relative to the first virtual machine. Other embodiments are disclosed.

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

Abstract: Implementations are provided herein for optimizing the usage of cluster resources in a cluster of nodes operating as a distributed file system. A node relative capacity table can be generated that inventories the total capacity of each node within the cluster of nodes. Each node can then be dynamically monitored for usage of node resources. A node available capacity table can be dynamically populated with the amount of available capacity each node has for compute, memory usage, and network bandwidth. When clients connect to the distributed file system, they can be directed to have their requests serviced by nodes with greater available capacity based on policy.

Abstract: Techniques are disclosed for identifying anomalies in small data sets, by identifying anomalies using a Generalized Extreme Student Deviate test (GESD test). In an embodiment, a data set, such as business data or a website metric, is checked for skewness and, if found to be skewed, is transformed to a normal distribution (e.g., by applying a Box-Cox transformation). The data set is checked for presence of trends and, if a trend is found, has the trend removed (e.g., by running a linear regression). In one embodiment, a maximum number of anomalies is estimated for the data set, by applying an adjusted box plot to the data set. The data set and the estimated number of anomalies is run through a GESD test, and the test identifies anomalous data points in the data set, based on the provided estimated number of anomalies. In an embodiment, a confidence interval is generated for the identified anomalies.

Abstract: Concepts and technologies disclosed herein are directed to virtual zones for Open Systems Interconnection (“OSI”) communication model layers 4-7 services in a cloud computing system. According to one aspect of the concepts and technologies disclosed herein, a cloud computing system can include a hardware resource and a virtual zone. The virtual zone can include a virtual network function (“VNF”) that is executable by the hardware resource. The VNF can support a service that operates within one of layers 4-7 of the OSI communication model. A computing system can detect new subscribers to the service within the virtual zone. The computing system also can determine that a capacity constraint exists within the virtual zone as a result of the new subscribers. The computing system also can home the new subscribers to the further virtual zone so that the further VNF can provide the service to the new subscribers.

Abstract: This disclosure involves allocating content-delivery resources to electronic content-delivery channels based on attribution models accuracy. For instance, a simulation is executed that involves simulating user exposures, times between user exposures, and user responses. The simulation is performed based on parameters associated with simulating user exposures to electronic content-delivery channels and user responses to the user exposures. An accuracy of a channel attribution model when estimating an attribution of an electronic content-delivery channel to a user response is evaluated based on the simulation. A channel attribution model is selected based on the evaluation. An attribution of the electronic content-delivery channel is determined by applying the selected channel attribution model to actual user exposures and actual user responses.

Abstract: Techniques are described for jointly modeling knowledge tracing and hint-taking propensity. During a read phase, a co-learning model accepts as inputs an identification of a question and the current knowledge state for a learner, and the model predicts probabilities that the learner will answer the question correctly and that the learner will use a learning aid (e.g., accept a hint). The predictions are used to personalize an e-learning plan, for example, to provide a personalized assessment. By using these predictions to personalize a learner's experience, for example, by offering hints at optimal times, the co-learning system increases efficiencies in learning and improves learning outcomes. Once a learner has interacted with a question, the interaction is encoded and provided to the co-learning model to update the learner's knowledge state during an update phase.

Abstract: Methods of forming a contact for a semiconductor device with double barrier layer sets, and a device so formed are disclosed. Methods may include: depositing a first metal layer contacting a semiconductor substrate in a contact opening; depositing a first nitride barrier layer on the first metal layer; and annealing after depositing the first nitride barrier layer to form silicide region in a junction area underlying the contact opening with the first metal layer and the semiconductor substrate. After the annealing, a second metal layer may be deposited, followed by a second nitride barrier layer. A conductor is formed in a remaining portion of the contact opening. The double barrier layer sets prevent the formation of volcano defects and also advantageously reduce contact resistance.

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: 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: 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: Scalable data storage techniques are described. In one or more implementations, data is obtained by one or more computing devices that describes fault domains in a storage hierarchy and available storage resources in a data storage pool. Operational characteristics are ascertained, by the one or more computing devices, of devices associated with the available storage resources within one or more levels of the storage hierarchy. Distribution of metadata is assigned by the one or more computing devices to one or more particular data storage devices within the data storage pool based on the described fault domains and the ascertained operational characteristics of devices within one or more levels of the storage hierarchy.

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.

Abstract: The present disclosure is directed toward systems and methods for identifying contributing factors associated with a multi-variable metric anomaly. One or more embodiments described herein identify one or more contributing factors that led to an anomaly in a multi-variable metric by calculating linearizing weights such that the total deviation in the multi-variable metric can be written as a weighted sum of deviations for dimension elements associated with the multi-variable metric.