Abstract: Disclosed herein are various embodiments directed to a device for minimally invasive medical treatment. The device being a hollow tube with a first end, a second end, and one or more anchors configured to extend outward from the exterior of the hollow tube. The hollow tube having a plurality of cutouts on the exterior, wherein the cutouts allow the hollow tube to be flexible. Additionally, the hollow tube may have at least one snap mechanism configured to connect the first end and the second end together.

Abstract: This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media, for network slice feasibility assessment for slice orchestration in a wireless network. Some aspects relate to providing on-demand approval or rejection of a requested network slice at a device associated with service management. The device may select respective resource allocations of the requested network slice for each cell of a set of cells in a wireless network, add the respective predicted resource allocations to respective current resource utilizations at each of the cells, and output a recommendation associated with the requested network slice in accordance with the summations. The device may select the respective resource allocations of the requested network slice in accordance with a service level agreement (SLA) of the requested network slice and, in some implementations, observed network conditions at each of the cells in the wireless network.

Abstract: Disclosed herein are techniques for creating and using tokens representing portions of programming code. Techniques include identifying a body of programming code; associating a plurality of tokens with respective portions of the body of programming code to generate a token-based representation of the body of programming code, wherein the associating comprises determining at least one canonical representation of at least one of the respective portions of the body of programming code; providing the token-based representation of the body of programming code to an emulator, the emulator being configured to interpret token-based representations; and receiving, from the emulator, an emulation result.

Abstract: Disclosed herein are techniques for training code language models. Techniques include making a plurality of programming code segments available to a code language processing model; providing an output of the code language processing model to one or more regression layers; determining, based on the one or more regression layers, a degree of functional similarity between two portions of the output; providing the degree of functional similarity to the code language processing model; and updating, based on the degree of functional similarity, the code language processing model.

Abstract: Disclosed herein are techniques for creating and using tokens representing portions of programming code. Techniques include identifying a first body of programming code associated with a hardware or software source attribute; associating a plurality of tokens with respective portions of the first body of programming code; configuring model input data for training a code language processing model customized in accordance with the hardware or software source attribute, the model input data comprising the plurality of tokens; and training, using the model input data, the code language processing model to analyze at least a part of the first body of programming code or a part of a second body of programming code, thus producing a customized and trained code language processing model in accordance with the hardware or software source attribute.

Abstract: Disclosed herein are techniques for dynamically predicting resource usage for code changes. Techniques include identifying an element of programming code; identifying a programming code execution environment; accessing a code language processing model, wherein the code language processing model has been trained to associate programming code execution tasks with amounts of computing resource usage; and predicting, without requiring execution of the element of programming code, an amount of computing resource usage associated with an execution of the element of programming code in the programming code execution environment.

Abstract: A method includes, in a user device (24) that runs an Operating System (OS-48), deciding to preload at least a User-Interface (UI) display of a user application (26). At least the UI display is preloaded in a simulated-foreground mode in which the UI display is (i) processed in a foreground mode by the user application, but (ii) kept in a background mode by the OS and hidden from a user of the user device.

Abstract: A method includes, in a processor (44) of a user device (24), preloading one or more user applications (26) in a background mode, in which activities associated with preloaded user applications are hidden from a user of the user device. An activity, which is invoked in the processor and is associated with a given preloaded user application, is detected. An assessment is made by the processor, whether the activity is a preload-initiated activity that is invoked due to preloading of the given user application, or whether the activity is a user-initiated activity that is invoked due to an action by the user. If the activity is assessed to be a preload-initiated activity, the activity is handled using a first handling scheme. If the activity is assessed to be a user-initiated activity, the activity is handled using a second handling scheme, different from the first handling scheme.

Abstract: A user device includes an interface and one or more processors. The interface is configured to communicate over a network. The one or more processors are configured to evaluate a pre-load scheduling condition with respect to a user application installed in the user device, and to schedule pre-loading of the user application depending on the pre-load scheduling condition.

Abstract: A user device includes an interface and one or more processors. The interface is configured to communicate over a network. The one or more processors are configured to evaluate a pre-load scheduling condition with respect to a user application installed in the user device, and to schedule pre-loading of the user application depending on the pre-load scheduling condition.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a network entity may calculate, using a machine learning (ML) model trained to estimate an impact of a reconfiguration of an antenna on a set of key performance indicators (KPIs) of a given cell and one or more neighbors of the given cell, one or more predicted KPIs using data characterizing a reconfiguration of a massive multiple-input multiple-output (M-MIMO) antenna. The network entity may provide the one or more predicted KPIs. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a network node may obtain a machine learning (ML) model trained to provide one or more predicted channel interference (CI) indicators informative of channel interference between cells of a cellular network. The network node may calculate, using the ML model, the one or more predicted CI indicators using data characterizing a given cell and one or more neighbor cells of the given cell. The network node may provide the one or more predicted CI indicators. Numerous other aspects are described.

Abstract: A method includes, in a user device (24) that runs an Operating System (OS-48), deciding to preload at least a User-Interface (UI) display of a user application (26). At least the UI display is preloaded in a simulated-foreground mode in which the UI display is (i) processed in a foreground mode by the user application, but (ii) kept in a background mode by the OS and hidden from a user of the user device.

Abstract: A user device includes a memory and one or more processors. The memory is configured to store one or more user applications installed in the user device. The one or more processors are configured to run an Operating System (OS) of the user device, including maintaining a data structure that tracks activity of the user applications, and to pre-load a user application before the user application is accessed by a user, including preventing the data structure from tracking the pre-loaded user application.

Abstract: A user device includes a memory and one or more processors. The memory is configured to store one or more user applications installed in the user device. The one or more processors are configured to select one or more operations, which are to be performed in normal launching of a user application but not in background pre-loading of the user application, to pre-load the user application before the user application is accessed by a user, including skipping the one or more selected operations, and to complete the one or more skipped operations in response to the user accessing the user application.

Abstract: A user device includes a display screen and one or more processors. The display screen is configured to display content to a user. The one or more processors are configured to pre-load a user application by running at least part of a program code of the user application in a background, including enabling the program code of the user application to pre-render a visual display of the user application in the background, and, in response to the user accessing the user application, to transfer the pre-rendered visual display to a foreground, thereby displaying the visual display to the user on the display screen.

Abstract: A user device (24) includes a display (56), audio circuitry (58) and a processor (44). The processor is configured to run an application that includes visual content and audio content, by: (i) before a user of the user device invokes the application, running the application in a background mode in which the visual content is not visible on the display, and inhibiting the audio content from being played by the audio circuitry, and (ii) after the user invokes the application, switching to run the application in a foreground mode in which the visual content is visible on the display, and permitting the audio content to be played by the audio circuitry.

Abstract: An apparatus for content delivery includes a network interface and one or more processors. The network interface is configured for communicating over a communication network. The one or more processors are configured to receive from a user of a user device a request to access a User-Interface (UI) unit that includes one or more content items, to initially display, in response to the request, the UI unit to the user with versions of the content items that are available for immediate display in the user device, regardless of whether the initially displayed versions are up-to-date or not, and, for at least a content item whose initially displayed version is not up-to-date, to obtain an up-to-date version of the content item, and merge the up-to-date version of the content item transparently to the user into the UI unit being displayed, to replace the initially displayed version.

Abstract: An apparatus for content delivery (20) includes a network interface (64) and one or more processors (44, 68). The network interface is configured for communicating over a communication network (32). The one or more processors are configured to receive from a user of a user device (24) a request to access a User-Interface (UI) unit that includes one or more content items, to initially display, in response to the request, the UI unit to the user with versions of the content items that are available for immediate display in the user device, regardless of whether the initially displayed versions are up-to-date or not, and, for at least a content item whose initially displayed version is not up-to-date, to obtain an up-to-date version of the content item, and merge the up-to-date version of the content item transparently to the user into the UI unit being displayed, to replace the initially displayed version.

Abstract: A method for content delivery includes selecting one or more time intervals. During each time interval among the selected time intervals, given content is prefetched from a content source to a communication terminal using a guaranteed prefetching mode, by continuously tracking the given content on the content source, so as to detect changes to the given content as they occur during the selected time interval, and maintaining the communication terminal continuously synchronized with the content source with respect to the given content, throughout the selected time interval, notwithstanding the changes that occur during the selected time interval, by continuously prefetching at least part of the given content from the content source to the communication terminal. Outside of the one or more selected time intervals, the given content is prefetched using a best-effort prefetching mode, by tracking the given content less frequently than the guaranteed prefetching mode.