Abstract: An augmented reality microscope (ARM) includes an objective lens, an eyepiece, an N-ocular observation tube, where N is a positive integer greater than 2, an image obtaining assembly physically connected to the N-ocular observation tube by a physical interface on the N-ocular observation tube, and an image projection assembly including, an image projection apparatus, a lens apparatus, and a light splitting apparatus. Light generated by an observed object during observation that enters an optical path through the objective lens and light generated by the image projection apparatus that enters the optical path through the lens apparatus converges at the light splitting apparatus in the image projection assembly, the converged light passes through the N-ocular observation tube.

Abstract: An apparatus, method and storage medium for controlling a pathologic microscope are provided. The method includes obtaining a pathological digital image from an incident optical path of the pathologic microscope; performing artificial intelligence (AI) analysis on the pathological digital image to generate AI analysis information; and controlling an augmented reality (AR) projection component to project the AI analysis information on a microscopic field of the pathologic microscope on an outgoing optical path.

Abstract: A gene regulatory relationship detection model training method performed by an electronic device, and relate to the field of biology technologies. The gene regulatory relationship detection model training method includes: obtaining material group data of a plurality of sample genes and an annotated regulatory relationship between at least one sample gene pair; determining a predicted probability that a regulatory relationship exists between each two sample genes among the plurality of sample genes by using a neural network model based on the material group data of the plurality of sample genes; and training the neural network model to obtain a gene regulatory relationship detection model, based on the annotated regulatory relationship between the at least one sample gene pair and the predicted probability between each two sample genes.

Abstract: This application provides a data processing method performed by an electronic device. The method includes: obtaining target data, and parsing the target data to obtain spatial location information and first feature information of each object in N objects; converting the target data into a first image based on the spatial location information and the first feature information of each object; extracting second feature information of each object in the target data from the first image; and performing preset processing on the second feature information of each object in the target data, to obtain a processing result of the target data. The entire data processing process is simple, occupies less computing resources, and has high data processing efficiency.

Abstract: This application provides a pathological section image processing method performed by a computer device. The method includes: obtaining stained images of a pathological section after cell membrane staining; determining cell nucleus positions of cancer cells in a stained image under an ith field of view in the n fields of view; generating a cell membrane description result of the stained image under the ith field of view, the cell membrane description result being used for indicating completeness and staining intensity of the cell membrane staining; determining quantities of cells of types in the stained image under the ith field of view according to the cell nucleus positions and the cell membrane description result; and determining an analysis result of the pathological section according to quantities of the cells of types in the stained images under the n fields of view.

Abstract: A method of making an anode material. The method begins by mixing a pre-passivated anode graphite with a supplement and a solvent to create a mixture. The solvent is then evaporated from the mixture to create a passivated anode graphite particle.

Abstract: Embodiments of this application disclose methods, systems, and devices for medical image analysis and medical video stream processing. In one aspect, a method comprises extracting video frames from a medical image video stream that includes at least two pathological-section-based video frames. The method also comprises identifying single-frame image features in the video frames, mapping the single-frame image features into single-frame diagnostic classification results, and performing a classification mapping based on a video stream feature sequence that comprises the single-frame image features. The classification mapping comprises performing a convolution operation on the video stream feature sequence through a preset convolutional layer, obtaining a convolution result in accordance with the convolution operation, and performing fully connected mapping on the convolution result through a preset fully connected layer.

Abstract: A 3D medical image recognition method and apparatus, a device, a non-transitory computer-readable storage medium, and a computer program product are provided, which relate to the field of artificial intelligence. View rearrangement processing is performed in an ith-round feature extraction process on an (i?1)th-round 3D medical image feature to obtain 2D image features. The (i?1)th-round 3D medical image feature is obtained by performing (i?1)th-round feature extraction on a 3D medical image. Different 2D image features are features of the (i?1)th-round 3D medical image feature in different views. Semantic feature extraction processing is performed on each 2D image feature in different views. Feature fusion processing is performed on the image semantic features to obtain an ith-round 3D medical image feature. Image recognition processing is performed on an Ith-round 3D medical image feature obtained through Ith-round feature extraction to obtain image recognition of the 3D medical image.

Abstract: The disclosed process relates to removal of benzene from a reformate stream and in turn providing gasoline and diesel products along with commodity chemicals (such as cyclohexylbenzene). The disclosed process further relates to the upgrading of heart-cut reformate benzene to higher value products.

Abstract: Methods for modifying a ZSM-5 zeolite by contacting the zeolite with an alkaline solution prior to combining with a binder material to produce a modified ZSM-5 catalyst extrudate that has substantially longer catalyst life, relative to an untreated ZSM-5 catalyst, for converting light olefins to products that may be used as a liquid transportation fuel blend stock. The alkaline solution is optionally sodium hydroxide. The binder is optionally alumina, bentonite or silica.

Abstract: An image generation method, apparatus, device, and storage medium. The method includes: obtaining contour information and target region information; determining at least one target contour according to the contour information and the target region information, the at least one target contour wholly or partly located in a target region; decreasing first coordinates of a plurality of contour points in the at least one target contour to obtain second location information, second location information of the at least one target contour includes second coordinates of a plurality of contour points in the at least one target contour, and the first coordinates of the plurality of contour points in the at least one target contour having a same decreasing extent; and generating a target image corresponding to the target region according to the second location information of the at least one target contour and the target region information.

Abstract: An image processing method and apparatus are provided. The method includes: acquiring a sample image, the sample image comprising an image obtained by image-capturing a sample within a preset optical waveband; processing a first image corresponding to at least one preset wavelength within the preset optical waveband in the sample image, to obtain a pseudo-color image; performing region division on the sample image according to a difference in sample element types in the sample image to obtain a region division result, the sample element types comprising a recognition element type; and determining an image region comprising the recognition element type from the sample image based on the pseudo-color image and the region division result.

Abstract: Methods that increase production of a liquid transportation fuel blend component by utilizing C5 hydrocarbon streams taken from both a refinery naphtha stream and an NGL fractionator pentanes plus stream. A high vapor pressure pentane fraction from the NGL fractionator is separated to remove isopentane and produce lower vapor pressure commodity natural gasoline. A refinery naphtha stream (that is optionally an FCC naphtha stream) is separated to produce a C5 olefins stream that is then oligomerized to produce an upgraded stream having lower vapor pressure and higher octane rating, then combined with the remainder of the naphtha stream as well as the isopentane stream to produce a gasoline blend component that meets specifications for vapor pressure and octane rating.

Abstract: The present subject matter relates to the field of machine learning and provides a classification and prediction method and apparatus, a device, a storage medium, and a computer program product. At least two pieces of data are acquired for a specified classification task. Each piece of data corresponds to one modality. A confidence corresponding to each of at least two modalities is acquired. The confidence indicates a classification and prediction probability of the modality in the specified classification task. Weighted fusion on data features of the at least two pieces of data is performed based on the confidence corresponding to each of the at least two modalities to obtain a fused feature. A prediction is performed according to the fused feature to obtain a classification and prediction result corresponding to the specified classification task.

Abstract: This application provides an image processing method and apparatus that can: acquire a target object through each narrow-band filter to obtain a narrow-band channel image including the target object; and fuse multiple narrow-band channel images in one-to-one correspondence with the multiple narrow-band filters to obtain a color image including a contour of the target object.

Abstract: An image acquisition model training method is contemplated. The method includes: acquiring a label image pair of a sample image; acquiring a predicted image pair of the sample image according to a first network model; adjusting the first network model based on the label image pair and the predicted image pair to obtain a second network model, so as to reduce a difference, obtained according to the second network model, between the predicted image pair and the label image pair; and determining the second network model as an image acquisition model in response to the second network model satisfying a training termination condition. By the above method, a heat map of an image in Hough space can be determined more quickly, and an image detection result can be determined based on the heat map of the image in the Hough space, thereby improving the accuracy of subsequent analysis processing.

Abstract: This application discloses an image clustering method performed by a computer device. This method includes: determining a first clustering parameter based on M image groups; for a target image group, dividing it into two image groups to obtain M+1 reference image groups, and determining a reference clustering parameter based on the M+1 reference image groups as a second clustering parameter for the target image group representing a clustering degree of images in the M+1 reference image groups; choosing, among respective second clustering parameters of the M image groups, a target second clustering parameter representing the highest clustering degree of images in the M image groups; and when the target second clustering parameter has a clustering degree not lower than the first clustering parameter, dividing a target image group corresponding to the target second clustering parameter into two image groups to obtain M+1 image groups.

Abstract: Disclosed are an image classification method performed by a computer device. The method includes: acquiring an image feature of a pathological image; extracting, for each scale in multiple scales, a local feature corresponding to the scale from the image feature; splicing the local features respectively corresponding to the scales to obtain a spliced image feature; and classifying the spliced image feature to obtain a category to which the pathological image belongs. According to the method provided in the embodiments of this application, the local features corresponding to different scales contain different information, so that the finally obtained spliced image feature contains feature information corresponding to different scales, and the feature information of the spliced image feature is enriched. The category to which the pathological image belongs is determined based on the spliced image feature, so that the accuracy of the category is ensured.

Abstract: A real-time online analysis device for substance pyrolysis, including: a pyrolyzing system (1), a capturing system (2), a testing system (3) and a controlling system (4) is disclosed. The pyrolyzing system (1), the capturing system (2) and the testing system (3) are connected with the controlling system (4). The capturing system (2) has a cooling cavity (22) and a heating cavity (23) inside. The temperature of the cooling cavity (22) ranges from room temperature to ?200° C., and the temperature of the heating cavity (23) ranges from room temperature to 1000° C. A method for real-time online analysis of substance pyrolysis using the device is also disclosed. The present device can provide real-time online pyrolysis, capturing, separation and analysis of substances at a plurality of temperature points or ranges.

Abstract: A real-time online analysis device for substance pyrolysis, including: a pyrolyzing system (1), a capturing system (2), a testing system (3) and a controlling system (4) is disclosed. The pyrolyzing system (1), the capturing system (2) and the testing system (3) are connected with the controlling system (4). The capturing system (2) has a cooling cavity (22) and a heating cavity (23) inside. The temperature of the cooling cavity (22) ranges from room temperature to ?200° C., and the temperature of the heating cavity (23) ranges from room temperature to 1000° C. A method for real-time online analysis of substance pyrolysis using the device is also disclosed. The present device can provide real-time online pyrolysis, capturing, separation and analysis of substances at a plurality of temperature points or ranges.