Abstract: Integrated circuit devices, methods, and circuitry for a timestamp engine to dynamically provision ports in accordance with PTP synchronization are provided. An integrated circuit device may include a number of ports configurable to communicate using timestamps corresponding to a number of Precision Time Protocol (PTP) clock domains. The integrated circuit may further include a timestamp engine configurable to receive timestamp requests and route a time of day (ToD) from a ToD circuit of a plurality of ToD circuits to different ports of the plurality of ports, where each ToD circuit is based on a PTP clock domain of the plurality of PTP clock domains.

Abstract: A fusion detection system includes the following elements. A data classification unit, for receiving several sensing data of several distributed devices, and classifying the sensing data as a first type, a second type, a third type and a fourth type. An anomaly detection unit, for performing an operation of an anomaly detection model based on the sensing data of the first type and the second type to generate an anomaly detection prediction result. A predictive maintenance unit, for performing an operation of a predictive maintenance model based on the sensing data of the first type, the second type, the third type and the fourth type and the abnormality detection prediction result to generate a predictive maintenance prediction result. A cost optimization unit, for performing an operation of a cost optimization model based on the predictive maintenance prediction result to generate a cost optimization decision.

Abstract: Integrated circuit devices, methods, and circuitry for a virtual time of day (ToD) engine to generate timestamps by using offsets associated with PTP clock domains. An integrated circuit device may include a number of ports configurable to communicate using timestamps corresponding to a number of Precision Time Protocol (PTP) clock domains. The integrated circuit device may also include a host data processing system to determine an offset for a first PTP clock domain of the plurality of PTP clock domains by calculating a difference between a first ToD provided by a clock source on the integrated circuit and one or more ToDs associated with the first PTP clock domain. The integrated circuit may further include a virtual ToD engine to generate a timestamp by adding the offset for the first PTP clock domain to a second ToD from the clock source and provide the timestamp to a port.

Abstract: A machine-learned predictive model is trained to predict potential for customer complaint. The model is part of an online concierge system. The online concierge system accesses a customer order that includes one or more items. The online concierge system determines input data for an item of the one or more items. The online concierge system determines a prediction value associated with potential for customer complaint for the item by applying the machine-learned prediction model to the input data. The online concierge system provides the prediction value to a picker client device associated with a picker who is assigned the item. The picker client device presents an alert to the picker based in part on the prediction value, and the alert includes a message that is customized to mitigate a cause of potential customer complaint for the item.

Abstract: A multi-gate hybrid-channel field-effect transistor (FET) structure of an integrated device like a nanosheet device or a forksheet device comprises a substrate layer, a first layer stack and a second layer stack arranged side by side on the substrate layer, a first and second additional semiconductor channel layer arranged respectively besides the second layer stack, and a dielectric wall arranged on the substrate layer between the first layer stack and the second layer stack. The first and second layer stack each comprise one or more semiconductor channel layers and gate layers stacked alternatingly with respective surfaces parallel to the surface of the substrate layer. Respective surfaces of the first and second additional semiconductor channel layer are parallel to each other and perpendicular to the surface of the substrate layer.

Abstract: Methods, non-transitory computer readable media, apparatuses, and systems for image and depth map generation include receiving a prompt and encoding the prompt to obtain a guidance embedding. A machine learning model then generates an image and a depth map corresponding to the image based on the guidance embedding. The image and the depth map are each generated based on the guidance embedding.

Abstract: A semiconductor structure and fabrication method is provided for gate all around (GAA) nanosheet devices. The semiconductor structure comprises a substrate, a gate stack on the substrate with a plurality of gate regions and silicon-based channel regions alternatingly arranged one on the other. A length of the gate regions is smaller than a length of the channel regions. Thus, pockets are formed on a side of the gate stack, each pocket being arranged next to one gate region and between the two channel regions adjacent to the gate region. Further, a silicon-based first contact region extends in a distance to the side of the gate stack, and a silicon-based filler material is arranged between the first contact region and the first side of the gate stack and in each first pocket.

Abstract: An image inpainting system is described that receives an input image that includes a masked region. From the input image, the image inpainting system generates a synthesized image that depicts an object in the masked region by selecting a first code that represents a known factor characterizing a visual appearance of the object and a second code that represents an unknown factor characterizing the visual appearance of the object apart from the known factor in latent space. The input image, the first code, and the second code are provided as input to a generative adversarial network that is trained to generate the synthesized image using contrastive losses. Different synthesized images are generated from the same input image using different combinations of first and second codes, and the synthesized images are output for display.

Abstract: In certain embodiments, a method of situationally updating a vehicle display includes causing, by a vehicle control system, a first view to be displayed on the vehicle display, where the first view includes a first display region. The method also includes receiving, by the vehicle control system, an information trigger in relation to a vehicle including the vehicle display. The method also includes, responsive to the information trigger, causing, by the vehicle control system, a second view to be displayed on the vehicle display. The second view includes the first display region together with a situational display region. The second view adjusts the first display region relative to the first view to accommodate the situational display region.

Abstract: The present invention discloses methods of inhibiting biofilm formation, increasing bacteriocidal activity within a biofilm, treating bacteria within a biofilm, or remediating a biofilm in or on a subject, comprising administering to the subject an effective amount of a compound according to Formula I: wherein R1-5 are defined herein.

Abstract: The disclosed computer-implemented method may include matching transportation requests. By collecting and batching match requests over an extended period, a dynamic transportation matching system may identify more efficient matches (e.g., may match transportation requests with greater overlaps). In addition, by dynamically setting and/or extending the upper bound of time that a transportation request may remain batched with other transportation requests, the dynamic transportation matching system may account for contextual information thereby situationally improving matching efficiencies made possible with higher upper bounds while avoiding requestor dissatisfaction, lost conversions, or other inefficiencies that may result from upper bounds that are too high.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: Routines are used to connect bot queries entered via a bot interface and database queries executed on a database. Each routine is associated with routine configurations, including (a) query attributes associated with bot queries that trigger the routine, (2) a database query executed or to be executed for the routine, and/or (3) display settings for displaying information returned from the database query in a bot response. Each routine is configured to generate an output structured data object (SDO) indicating information returned from the database query and the display settings applicable to the information. The output SDOs from the various routines are transmitted to the bot application via a single API endpoint. The routine configurations are entered by a design user through one or more design user interfaces rendered by an integrative configuration application module.

Abstract: The present technology provides compounds of Formula I and related methods for treating a bacterial infection as well as methods for inhibiting interaction of a bacterioferritin and a bacterioferritin-associated ferredoxin.

Abstract: A vehicle includes an output device configured to communicate to a driver of the vehicle and an in-vehicle control system. The in-vehicle control system is configured to evaluate one or more trigger inputs including at least one of a current dynamic state of the vehicle or an attribute of an environment of the vehicle. The in-vehicle control system processes the one or more trigger inputs according to a dynamic model having a state with a time-dependent response to changes in the one or more trigger inputs. The state of the dynamic model is evaluated with respect to a threshold condition. In response to the dynamic model satisfying the threshold condition, guidance is provided to the driver through the output device.

Abstract: A modeling system accesses a two-dimensional (2D) input image displayed via a user interface, the 2D input image depicting, at a first view, a first object. At least one region of the first object is not represented by pixel values of the 2D input image. The modeling system generates, by applying a 3D representation generation model to the 2D input image, a three-dimensional (3D) representation of the first object that depicts an entirety of the first object including the first region. The modeling system displays, via the user interface, the 3D representation, wherein the 3D representation is viewable via the user interface from a plurality of views including the first view.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize a text-image alignment loss to train a diffusion model to generate digital images from input text. In particular, in some embodiments, the disclosed systems generate a prompt noise representation form a text prompt with a first text concept and a second text concept using a denoising step of a diffusion neural network. Further, in some embodiments, the disclosed systems generate a first concept noise representation from the first text concept and a second concept noise representation from the second text concept. Moreover, the disclosed systems combine the first and second concept noise representation to generate a combined concept noise representation. Accordingly, in some embodiments, by comparing the combined concept noise representation and the prompt noise representation, the disclosed systems modify parameters of the diffusion neural network.

Abstract: A method, apparatus, and non-transitory computer readable medium for image generation are described. Embodiments of the present disclosure obtain a content input and a style input via a user interface or from a database. The content input includes a target spatial layout and the style input includes a target style. A content encoder of an image processing apparatus encodes the content input to obtain a spatial layout mask representing the target spatial layout. A style encoder of the image processing apparatus encodes the style input to obtain a style embedding representing the target style. An image generation model of the image processing apparatus generates an image based on the spatial layout mask and the style embedding, where the image includes the target spatial layout and the target style.

Abstract: A method, non-transitory computer readable medium, apparatus, and system for image generation are described. An embodiment of the present disclosure includes obtaining an input image, an inpainting mask, and a plurality of content preservation values corresponding to different regions of the inpainting mask, and identifying a plurality of mask bands of the inpainting mask based on the plurality of content preservation values. An image generation model generates an output image based on the input image and the inpainting mask. The output image is generated in a plurality of phases. Each of the plurality of phases uses a corresponding mask band of the plurality of mask bands as an input.

Abstract: A method for predicting outcome of a process used for manufacturing a sample in a bioreactor, the process belonging to a category. The method comprises selecting a process model based on the category; accessing historic data related to past process runs for manufacturing the sample; accessing current data obtained from a current process run of the process. The obtained current data, which is based on the selected process model, comprises: process strategy data, bioreactor instrument data, data from online sensors and/or data from offline sensors. The method further comprises predicting an outcome of at least one selected parameter of the current process run for manufacturing the sample based on the accessed historic data and current data.