Abstract: Systems and methods are described for providing a GUI for representing tunnels and stretched networks in a virtual entity pathway virtualization. In an example, an application can obtain data related to physical and virtual entities in a stretch network and build a model of the stretch network using the data. The model can be based on a flow of network traffic between two entities. The application can render a GUI that illustrates the flow of traffic between two entities, including any datacenters, physical entities, and virtual entities involved in the network flow. The GUI can display the entities in a way that shows which virtual extensible local area network is being used to transfer the network traffic at each step in the network flow. The GUI can also display icons representing remote tunnel endpoints that show how network traffic is transferred between datacenters.

Abstract: An artificial tissue construct for nerve repair and regeneration includes a biocompatible and biodegradable nerve guidance matrix comprising a plurality of biopolymers that include chitosan, gelatin, collagen and hyaluronic acid. A cross-linker includes glutaraldehyde. The nerve guidance matrix is formed as a three-dimensional scaffold polyelectrolyte complex (PEC). A subconfluent and grown monolayer of at least one of human mesenchymal stem cells, mesenchymal stem cells, differentiated Schwann cells and neuronal cells is on the biocompatible and biodegradable nerve guidance matrix for direct implantation or delivery. A method of making the artificial tissue construct is disclosed.

Abstract: Subject matter disclosed herein relates to monitoring and/or controlling blood glucose levels in patients. In particular, times for obtaining metered blood glucose samples of a patient may be altered based, at least in part, on a blood glucose level of said patient observed from a blood glucose sensor.

Abstract: Systems and methods for identifying and evicting idle sessions include training a machine learning model as a session classifying model to learn rules for classifying active sessions between clients and the cloud-based service. The session classifying model is trained to receive a plurality of parameters pertaining to the document associated with an active session as input and to apply the rules to the plurality of parameters to determine a classification for the active session and to provide an output indicative of the classification for the active session. The session classifying model is then utilized in the cloud-based service to classify the active sessions. The active sessions classified as idle sessions may then be evicted from the cloud-based service.

Abstract: Among other things, the present disclosure relates to designed oligonucleotides, compositions, and methods thereof. In some embodiments, provided oligonucleotide compositions provide altered splicing of a transcript. In some embodiments, provided oligonucleotide compositions have low toxicity. In some embodiments, provided oligonucleotide compositions provide improved protein binding profiles. In some embodiments, provided oligonucleotide compositions have improved delivery. In some embodiments, provided oligonucleotide compositions have improved uptake. In some embodiments, the present disclosure provides methods for treatment of diseases using provided oligonucleotide compositions.

Abstract: A data-driven algorithm including various network analysis routes to characterize the production of known and putative specialized metabolites and unknown analytes triggered by different exogenous compounds. Bipartite networks quantify the relationship between metabolites and treatments stimulating their production through two routes. A direct route determines the production of known and putative specialized metabolites induced by a treatment. An auxiliary route is specific for unknown analytes. Various network centrality metrics rank treatments based on their ability to trigger a broad range of specialized metabolites. The specialized metabolites are ranked based on their receptivity to various treatments. This enables tracking the influence of any exogenous treatment or abiotic factor on metabolomics output for targeted metabolite research.

Abstract: A Janus G-C base as building block for a triazine based self-assembly of formula (I), a process for the preparation, and its application in developing supramolecular polymers, peptide nucleic acids (PNAs) and smart polymers thereof. A triazine based self-assembly of formula (I): wherein, ‘R’ is selected from the group comprising of linear or branched unsubstituted and substituted C1-C7 alkyl, unsubstituted and substituted aryl, unsubstituted and substituted natural amino acids which may be protected, linear or branched unsubstituted and substituted C1-C7 alcohols, or linear or branched unsubstituted and substituted C1-C7 amines.

Abstract: Provided is a method for suggesting a caption for an image, comprising: receiving the image; determining a plurality of impacting categories associated with a plurality of contextual keywords for the image, each of the plurality of impacting categories representing a sentiment associated with the plurality of contextual keywords; grouping the plurality of contextual keywords into a plurality of groups based on the plurality of impacting categories; determining an order associated with the plurality of contextual keywords, based on a pre-determined impacting function; generating at least one caption by processing each contextual keyword, based on the order associated with the plurality of contextual keywords; determining a priority value associated with each of the at least one caption based on information associated with the corresponding caption, a user profile, and the image; and suggesting the caption from the at least one caption based on the priority value.

Abstract: State of the art approaches used to address security aspects in serverless platforms perform workflow validations on an end to end flow, however, this cannot prevent attacks targeted at intermediate function calls in the workflow. Further, the existing systems store policy data in insecure manner, which causes security issues. The disclosure herein generally relates to serverless clouds, and, more particularly, to a method and system for privacy-preserving workflow validations in serverless clouds. The system stores policy data in a secured/encrypted manner. The system also performs validations at different levels, at a first level to allow/deny access at an ingress point, and at a second level to allow/deny access at critical intermediate points. This approach thus provides safety against attacks that may have been initiated post initial validation, and offers added data security.

Abstract: Techniques for data lifecycle discovery and management are presented. Data lifecycle discovery platform (DLDP) can identify data of users, data type, and language of data stored in data stores (DSs) of entities based on scanning of data from databases. DLDP determines compliance of DLDP and DSs with obligations relating to data protection arising out of jurisdictional laws or agreements. DLDP generates rules to facilitate complying with and enforcing laws and agreements. DLDP can determine, and present to authorized users, risk scores relating to levels of compliance of the DLDP, associated platforms, or entities, risk indicator metrics, or a privacy health index of the organization associated with DLDP. DLDP can manage user rights regarding data, and access to data in DSs and information relating thereto stored in secure data store of DLDP. DLDP can remediate issues involving anomalies indicating non-compliance. DLDP can utilize machine learning to enhance various functions of DLDP.

Abstract: The invention proposes a method and system for deriving real-time insights about heterogeneous infrastructure by allowing a user to post a natural language query. A natural language processing (NLP) engine converts the natural language query into a computer identifiable query. A query engine (QE), based on the computer identifiable query, predicts diverse infrastructure-specific commands. The QE utilizes Machine Learning (ML) models to understand the intent of the natural language query and predict the diverse infrastructure-specific commands. The QE transforms and forwards the infrastructure-specific commands to corresponding components of the heterogeneous infrastructure. One or more sensors integrated with the components of the heterogeneous infrastructure receive query from the QE and respond to the queries in real-time. An interpreter module converts the responses received from the sensors into a common data format and derives insights from the converted responses and transmits them to the user device.

Abstract: Techniques for data lifecycle discovery and management are presented. Data lifecycle discovery platform (DLDP) can identify data of users, data type, and language of data stored in data stores (DSs) of entities based on scanning of data from databases. DLDP determines compliance of DLDP and DSs with obligations relating to data protection arising out of jurisdictional laws or agreements. DLDP generates rules to facilitate complying with and enforcing laws and agreements. DLDP can determine, and present to authorized users, risk scores relating to levels of compliance of the DLDP, associated platforms, or entities, risk indicator metrics, or a privacy health index of the organization associated with DLDP. DLDP can manage user rights regarding data, and access to data in DSs and information relating thereto stored in secure data store of DLDP. DLDP can remediate issues involving anomalies indicating non-compliance. DLDP can utilize machine learning to enhance various functions of DLDP.

Abstract: Provided is a method and system (108) for building and leveraging a knowledge fabric (110) in a Software Development Lifecycle (SDLC). A plurality of SDLC artifacts are received from a plurality of heterogeneous data sources (102). The plurality of SDLC artifacts are then correlated to build an end-to-end correlation and are clustered to generate an SDLC knowledge fabric (110). This includes extracting semantic and contextual data from the plurality of SDLC artifacts using Natural Language Processing (NLP) and deep text analytics and transforming the extracted semantic and contextual data to knowledge graphs. One or more actionable items (112) are then derived using the SDLC knowledge fabric (110) and the one or more actionable items (112) are used to improve overall process efficiency and accelerate software delivery in the SDLC.

Abstract: A method for generating a signal for a device process may include retrieving a reduced-memory template signal centered on a chosen subharmonic of a reconstruction sample rate, upsampling the reduced-memory template signal to generate the signal for the device process at a desired data rate, and communicating the signal to a transducer for playback by the transducer.

Abstract: Systems for use at a valve disposed between an atrium and a ventricle of a heart of a subject comprise an implant comprising a first anchoring assembly and a second anchoring assembly, each of the anchoring assemblies comprising multiple anchors, and a connector, connecting the multiple anchors to each other. A bridge couples the first anchoring assembly to the second anchoring assembly, and has an adjustable bridging length. A driver is transluminally advanceable to the atrium, and is configured to use the anchors of the respective anchoring assembly to anchor each of the respective anchoring assemblies to an opposing side of the valve, such that the bridge spans at least partway across the valve. The distance between the first and second anchoring assemblies is adjustable using a tool to adjust the bridging length of the bridge. Other embodiments are also described.

Abstract: Various embodiments of the present technology include an improved system for measuring the impacts of feature rollouts on machine utilization and service performance. More specifically, embodiments of the present technology include an exposure control system based on randomized machine assignments and a corresponding score card for comparing machine utilization metrics. In an embodiment, a computing apparatus identifies a new feature in a codebase, wherein the codebase has been updated with the new feature across multiple resources, enables the new feature for a target group of the multiple resources while keeping the new feature dormant for a control group of the multiple resources, collects performance information for the target group and the control group for a time period, and generates a visualization of one or more differences between the performance information for the target group and the performance information for the control group for the time period.

Abstract: A vascular access system can include a port configured to be implanted outside of a target body lumen, at least one conduit fluidly connected to the port, and at least one one-way valve proximate the distal end of the conduit and within the fluid pathway of the sidewall of the conduit. The system can also include a gateway element comprising a through lumen operably connected to an outer diameter of the conduit, the gateway element comprising a first radially compressed configuration in which the gateway element causes occlusion within the through lumen, and a second radially expanded configuration in which the gateway element permits passage of fluids within the through lumen.

Abstract: The present invention describes a non-invasive assay based on a key biomarkers that can be used to create a Radiation Response Index indicative of the tumor's response to radiation therapy prior to, during, and post-radiation therapy. The invention stratifies the subjects into clinically relevant categories, Radiation Resistant and Radiation Sensitive.

Abstract: Systems and methods for providing metric data for patterns in a modeling environment are disclosed. In some aspects, contexts for generating metric data for a pattern are constructed. The pattern represents one or more computations executable in the modeling environment and associated with operation or behavior of a real-world system. The contexts include information about the pattern. The metric data is associated with one or more objectives with which the use of the pattern is associated. Code for the pattern for each context is generated. Metric data is generated for the pattern and under each context. The metric data of the pattern under each context is associated with the objectives. The metric data and the association are stored for use in providing information about or based on the metric data when the pattern is to be or is used in a model representing the real-world system.