Abstract: By example, a method for training a model to segment test images, wherein the test images comprise ultrasound image data, includes: receiving, at a self-supervised learning framework, a first plurality of training images, wherein the first plurality of training images include ultrasound data corresponding to patients' livers; processing the first plurality of plurality of training images with a learning algorithm of the self-supervised learning framework, and responsively adapting a trained model; and receiving, at a supervised learning framework, the trained model and a second plurality of training images, wherein the second plurality of training images include ultrasound data corresponding to patients' livers and annotations of the livers, and responsively adapting the trained model.

Abstract: A cooking assembly can include a cooking vessel, a mixer, and a motor. The cooking vessel can include a bottom contact portion including a first bore therethrough, a heating portion spaced above the bottom contact portion and including a second bore therethrough, and a sidewall connected to the heating portion and together with the heating portion configured to retain food in the cooking vessel. The mixer can be located within the cooking vessel, where the mixer configured to rotate relative to the heating portion. The motor can be connected to the mixer via the first bore and the second bore to drive the mixer to rotate.

Abstract: By example, a method includes: receiving ultrasound image data of a patient, including a segmented region corresponding to a liver; automatically identifying an area for a region of interest within the segmented region, wherein the region of interest corresponds to a region in the liver for performing shear-wave elastography; and presenting, on a display, the ultrasound image data and the area for the region of interest.

Abstract: An atomizing core, an atomizer, an electronic cigarette, and an assembly method are provided. The atomizing core is used for atomizing an atomizing substrate to form an aerosol, and includes: an atomizing core housing defining an airflow inlet, an airflow outlet, an accommodating space between the airflow inlet and the airflow outlet, and at least one atomizing substrate inlet in communication with the accommodating space; an atomizing seat arranged in the accommodating space and defining an atomizing channel for being in communication with the airflow inlet and the airflow outlet, and at least one opening for communicating the at least one atomizing substrate inlet with the atomizing channel; and at least one heating sheet arranged in the atomizing channel and at least partially opposite one or more of the at least one opening respectively. Embodiments of the present disclosure can increase the degree of integration of the atomizing core, so as to increase production efficiency and product stability.

Abstract: An atomization core provides a core body having a central channel, a first cylindrical portion having an outer diameter, and a second cylindrical portion having an outer diameter. The central channel extends through the first and second cylindrical portions, and the first cylindrical portion, the second cylindrical portion, and the central channel are aligned about a central axis. The outer diameter of the second portion is larger than the outer diameter of the first portion.

Abstract: A box assembly for an aerosol-generating device including a body portion and a cover portion disposed over the body portion. The body portion includes a sidewall, an accommodating cavity, and a first filling port disposed on the sidewall. The first filling port is configured to align and communicate with a filling port of the aerosol-generating device when the aerosol-generating device is disposed within the accommodating cavity. The box assembly is placed in a rack assembly, to provide an aerosol-forming substance for the aerosol-generating device.

Abstract: Systems and methods for uses and/or improvements to artificial intelligence applications, particularly in the realm of code development. As one example, systems are described herein for an artificial intelligence tool for software code development that estimates runtime processing efficiency of serverless applications as well as provide recommendations for more efficient code for the serverless applications.

Abstract: A system and method are disclosed for training a machine learning model configured to determine a traversability of a real-world environment by a mobile robot based on an image of the real-world environment. The method advantageously generates high quality synthetic training data for training a traversability detection model to discriminate between traversable and untraversable regions in images captured of a real-world environment. The synthetic training data is generated through simulation of a virtual robot in a virtual environment. Once the traversability detection model is trained, it can be deployed to the mobile robot for the purpose of predicting traversability of a real-world environment.

Abstract: Methods for operating a mobile robot to dynamically offload computation tasks to a cloud system are described. The methods advantageously enable a mobile robot to switch between local execution by the mobile robot or remote execution by the cloud system at any time, depending on timing requirements, energy requirements, or any other requirements. Thus, the methods enable the mobile robots to be robust to varying network conditions, while at the same time taking advantage of off-board computing resources when possible. In at least some embodiments, a middleware such as Robot Operating System is leveraged for communication between mobile robots and with the cloud system.

Abstract: A mobile robot system is described in having a mobile robot and cloud system. The mobile robot leverages cloud computing to offload Neural Radiance Fields (NeRF) based 3D scene reconstruction. The mobile robot advantageously adopts techniques for view filtering and next-best view selection that optimize the image collection process necessary for training an NeRF model with the cloud system. These techniques enable the mobile robot to discard redundant images that do not provide significant new information about the environment. Additionally, these techniques enable the mobile robot to strategically select next-best views that maximize the information gain, while minimizing a total number of images required and the time required to capture the images. These techniques provide a significant reduction in the overall bandwidth required for providing image data to the cloud system and can result in a more accurate and higher quality 3D reconstruction of the environment.

Abstract: An access device for accessing an intervertebral disc having an outer shield comprising an access shield with a larger diameter (˜16-30 mm) that reaches from the skin down to the facet line, with an inner shield having a second smaller diameter (˜5-12 mm) extending past the access shield and reaches down to the disc level. This combines the benefits of the direct visual microsurgical/mini open approaches and the percutaneous, “ultra-MIS” techniques.

Abstract: A method of placing an implant for intervertebral fusion between adjacent vertebral bodies in a patient includes inserting the implant in a space between the adjacent vertebral bodies such that both a first intervertebral spacer body and a second intervertebral spacer body contact each of the adjacent vertebral bodies. The first intervertebral spacer body is spaced apart from the second intervertebral spacer body. An expandable container portion of the implant disposed between the first intervertebral spacer body and the second intervertebral spacer body is filled with fill material such that the expandable container expands to contact each of the adjacent vertebral bodies.

Abstract: An access device for accessing an intervertebral disc having an outer shield comprising an access shield with a larger diameter (˜16-30 mm) that reaches from the skin down to the facet line, with an inner shield having a second smaller diameter (˜5-12 mm) extending past the access shield and reaches down to the disc level. This combines the benefits of the direct visual microsurgical/mini open approaches and the percutaneous, “ultra-MIS” techniques.

Abstract: A box assembly includes a body portion; a tray disposed within the body portion; and a cover disposed over the tray and body portion. The body portion includes a first filling port at one end, and the tray includes a second filling port aligned with the first filling port. A rack assembly can hold a plurality of box assemblies. The rack assembly can be held by an e-liquid filling apparatus for filling a device contained within each box assembly with e-liquid.

Abstract: An e-liquid filling apparatus is configured to provide e-liquid to at least one device having a reservoir configured to hold an e-liquid, and an e-liquid filling inlet in communication with the reservoir. The e-liquid filling device includes a workbench configured to hold the at least one device, and an e-liquid filling assembly configured to provide e-liquid to the at least one device. The e-liquid filling apparatus also includes a moving assembly configured to adjust a position of a filling portion of the e-liquid filling assembly and the at least one device relative to each other, and a control assembly configured to control operation of the e-liquid filling apparatus.

Abstract: A mouthpiece assembly for an e-cigarette device provides a mouthpiece cover, a tubular mouthpiece fastener, and a mouthpiece ring having a central aperture. The mouthpiece fastener is configured to extend through the central aperture of the mouthpiece ring to snap-fit engage the mouthpiece cover.

Abstract: A method for managing network segmentation policies in a cloud computing environment. The method includes collecting metadata associated with cloud resources protected by multiple segmentation policies. Relationships between the cloud resources are determined based on the collected metadata and visualized on a Graphical User Interface (GUI). These relationships are then recorded in a database. The method automatically configures a network segmentation policy based on the determined relationships, controlling whether network traffic between cloud resources is allowed or denied. The policy is then enforced by allowing or blocking traffic to and from the cloud resources based on the configured segmentation rules.