Abstract: A process and system for the conversion of a feedstock comprising C3-C5 light alkanes to a C5+ hydrocarbon product, for example, a BTX-rich hydrocarbon product, by performing the alkane activation (first-stage) and the oligomerization/aromatization (second-stage) in separate stages, which allows each conversion process to occur at optimal reaction conditions thus increasing the overall hydrocarbon product yield. The alkane activation or first-stage is operated at a higher temperature than the second-stage since light alkanes are much less reactive than light olefins. Since aromatization of olefins is more efficient at higher pressure, the second-stage is maintained at a higher pressure than the first-stage. Further, fixed-bed catalysts are used in each of the first-stage and the second-stage.

Abstract: This disclosure relates to a model training method and apparatus and an image processing method and apparatus. The model training method includes: obtaining a first sample image and a first standard region proportion corresponding to a first object in the first sample image; obtaining a standard region segmentation result corresponding to the first sample image based on the first standard region proportion; and training a first initial segmentation model based on the first sample image and the standard region segmentation result, to obtain a first target segmentation model.

Abstract: A computer device obtains a medical image set. The device identifies a difference between the reference medical image and the target medical image to obtain a candidate non-lesion region in the target medical image. The device determines area size information of the candidate non-lesion region as candidate area size information. The device adjusts the candidate non-lesion region according to the annotated area size information when the candidate area size information does not match the annotated area size information, so as to obtain a target non-lesion region in the target medical image.

Abstract: Techniques involve: determining use levels of task types associated with corresponding storage layers in multiple storage layers based on respective current resource use statuses of the multiple storage layers, where the multiple storage layers share physical resources, and tasks are executed on the corresponding storage layers in accordance with respective task types; determining respective priority levels of the multiple task types based on respective historical resource use statuses of the multiple storage layers; and selecting one group of tasks for execution based on the use levels and priority levels of the multiple task types and task types that the multiple to-be-executed tasks belong to, where the number of tasks belonging to each task type in the one group of tasks is determined by the use level of the corresponding task type, and the one group of tasks is sorted in accordance with corresponding priority levels of respective task types.

Abstract: Embodiments of this application provide omics data processing method and apparatus based on a graph neural network, a device and a medium, and relate to medical, artificial intelligence, cloud data and other technical fields. The method includes: acquiring first omics data of a target object; extracting, at least two first omics features from the first omics data; determining, a first correlation between different omics features; constructing based on the at least two first omics features and the first correlation, a first graph structure corresponding to the first omics data, the first graph structure comprising at least two nodes and at least one connecting edge; obtaining, a node feature of each node in the first graph structure through a first graph neural network based on the first graph structure; and performing medical analysis on the target object based on the node feature.

Abstract: An artificial intelligence-based image processing method implemented by a computer device is provided. The method includes: acquiring an image; performing element region detection on the image to determine an element region in the image; detecting a target element region in the image using an artificial intelligence-based technique; generating a target element envelope region by searching an envelope for the detected target element region; and fusing the element region and the target element envelope region to obtain a target element region outline.

Abstract: A process for activating a hydrogenation catalyst comprising nickel to produce a selective hydrogenation catalyst, comprising contacting the hydrogenation catalyst with a mixed gas comprising and hydrogen sulfide and periodically increasing the temperature of the mixed gas in increments until the mixed gas reaches a temperature that facilities the efficient catalytic hydrogenation of both acetylene and butadiene by the modified catalyst, while the modified catalyst is simultaneously characterized by low selectivity for the hydrogenation of ethylene. The disclosure further claims a process that utilizes the modified catalyst to selectively hydrogenate acetylene and butadiene contaminants in a raw light olefin stream produced by thermal cracking, thereby extending the useful catalytic lifespan of a downstream oligomerization catalyst that converts the light olefins stream to a liquid transportation fuel, or a blend stock thereof.

Abstract: This application provides an artificial intelligence-based pathological image processing method performed by an electronic device. The method includes: determining a seed pixel of an immune cell region from a pathological image; obtaining a seed pixel mask image corresponding to the seed pixel of the immune cell region from the pathological image based on the seed pixel of the immune cell region; segmenting an epithelial cell region in the pathological image, to obtain an epithelial cell mask image of the pathological image; fusing the seed pixel mask image and the epithelial cell mask image of the pathological image, to obtain an effective seed pixel mask image corresponding to the immune cell region in the pathological image; and determining a ratio value of the immune cell region in the pathological image based on the effective seed pixel mask image.

Abstract: Disclosed are an attenuation system and the use thereof for attenuating plasmodia, specifically the use of an EF1g gene for attenuating plasmodia. The attenuation system regulates the expression or degradation of the EF1g gene by using a regulatory system, thereby controlling the growth of plasmodia and achieving the attenuation of plasmodia.

Abstract: A storage management technique involves: determining a spare degree of physical storage space of a file system and access characteristics of the file system; determining, using a provision operation classification model and based on the spare degree and the access characteristics, a target storage provision operation to be performed for the file system from multiple storage provision operations, wherein the multiple storage provision operations include at least a storage space expansion operation and a storage space reclamation operation, and the provision operation classification model characterizes an association relationship between different spare degrees and different access characteristics of the file system and the multiple storage provision operations; and performing the determined target storage provision operation for the file system. Accordingly, a better balance is achieved between storage efficiency and I/O performance.

Abstract: A microscope system includes an objective lens, configured to gather a first light of a target sample to enter a first optical path, wherein the first light converges, at a beamsplitter, with a second light generated by an image projection module after entering the first optical path through a lens assembly; a beamsplitter assembly, configured to respectively separate and cast light in different optical paths; a camera assembly, configured to photograph the target sample in a microscope field of view, to photograph a clearly focused image through a first optical path by using the camera assembly; an auxiliary focusing device, configured to determine a focal length matching the camera assembly; and a focusing device, configured to adjust a focal length of image light entering the camera assembly according to a defocus amount of a target sample image determined by the auxiliary focusing device.

Abstract: A process for methanation comprising a first region for flowing a stream over a solid oxide electrolysis cell. In this first region the stream consists of CO2, H2, and H2O, the stream is converted into a first conversion stream, and the solid oxide electrolysis cell is enhanced with a methanation catalyst. The process also has a removal region connected to the first region wherein the removal region is able to flow the first conversion stream away from the solid oxide electrolysis cell.

Abstract: This application relates to a method for reporting UDC information by UE, and a device. The method includes: A terminal device receives request information sent by a network device, where the request information is used to request the terminal device to report first information; and the terminal device sends the first information to the network device, where the first information is used to indicate that the terminal device supports a UDC capability, and indicate a maximum quantity of DRBs that can be simultaneously supported by the terminal device and for which UDC is activated.

Abstract: A communication method includes that a first device deletes a first data packet. The first device sends first signaling to a second device, where the first signaling includes or indicates a first buffer, the first buffer is used to compress a second data packet or used to decompress a compressed second data packet, a serial number of the first data packet and a serial number of the second data packet are consecutive, the serial number of the second data packet follows the serial number of the first data packet, and the second device is a receiving device of the compressed second data packet.

Abstract: Aspects of the disclosure are directed to the field of artificial intelligence technologies and provides a method and an apparatus for obtaining a feature of duct tissue based on computer vision, an intelligent microscope, a storage medium, and a computer device. The method can include the steps of obtaining an image including duct tissue, determining, in an image region corresponding to the duct tissue in the image, at least two feature obtaining regions adapted to duct morphology of the duct tissue, obtaining cell features of cells of the duct tissue in the feature obtaining regions respectively, and obtaining a feature of the duct tissue based on the cell features of the cells of the duct tissue in the feature obtaining regions respectively.

Abstract: A method is provided and includes acquiring a digital slide comprising objects of at least two sizes, the objects including a first object of a first size and a second object of a second size different from the first size, for each of the first object and the second object, acquiring images of a corresponding object in at least two scales based on the digital slide, where the acquired images of the corresponding object in the at least two scales include an image of a larger scale and an image of a smaller scale, the image of the larger scale having a smaller image size and a higher image resolution than the image of the smaller scale, and determining, from the images of the corresponding object in the at least two scales, an image having an image size that corresponds to a size of the corresponding object.

Abstract: A no-gap measurement capability reporting method includes receiving, by a first device, a first message from a second device, where the first message instructs the first device to determine a gap measurement; and sending, by the first device, a second message to the second device based on the first message, where the second message indicates a no-gap measurement capability.

Abstract: This application discloses an artificial intelligence-based image processing method, apparatus, device, and storage medium, and relates to the field of computer technology. The method includes: obtaining a slice image; dividing the slice image to obtain a plurality of image blocks; feeding the plurality of image blocks into a labeling model, extracting, by the labeling model, a pixel feature of the slice image based on the plurality of image blocks, determining a plurality of vertex positions of a polygonal region in the slice image based on the pixel feature, concatenating the plurality of vertex positions, and outputting label information of the slice image, the polygonal region being a region in which a target pathological tissue of interest is located.

Abstract: A communication method includes a first device configuring a plurality of buffers to compress data packets. Each of the plurality of buffers is used to compress one or more data packets for transmission. If a compressed data packet is lost during transmission, a receive end cannot decompress a data packet corresponding to a same buffer as the lost data packet, but the receive end can continue to decompress a data packet that does not correspond to the same buffer as the lost data packet.

Abstract: This application discloses a spatial positioning method and related apparatus, and a navigation stick.