Abstract: A trace detection device including: an ion mobility tube ; a sampling gas path module ; a sample injection gas path module configured to introduce a sample carrier gas containing a sample collected by the sampling gas path module toward the ion mobility tube; and a gas chromatography apparatus capable of pre-separating the sample carrier gas, so as to form a pre-separated sample carrier gas; wherein the sample injection gas path module is further configured to be capable of switching between a first mode and a second mode, in the first mode, the sample injection gas path module introduces the sample carrier gas into the ion mobility tube; and in the second mode, the sample injection gas path module introduces the sample carrier gas into the gas chromatography apparatus to pre-separate the sample carrier gas, and the pre-separated sample carrier gas is introduced into the ion mobility tube.

Abstract: Provided are an odor sniffing device (11) and a vehicle-mounted security inspection apparatus for a container (1). The odor sniffing device (11) includes a primary sampling front end (116), which has a vent adapter (116-1) having a shape matching with a vent of the ventilator of the container, so that when the primary sampling front end (116) fits with the ventilator, the vent adapter (116-1) and the vent generally cooperate to achieve fluid communication. The vehicle-mounted security inspection apparatus (1) may perform imaging inspection and chemical inspection simultaneously.

Abstract: The first core includes a main body part extending in a first direction along a main surface of the substrate, a first foot part extending from the main body part to the second core through the substrate, and a second foot part extending from the main body part to the second core through the substrate at a position at which the coil conductor is sandwiched between itself and the first foot part in the first direction, and the insulating member includes a bottom wall part interposed between at least the first foot part and the second core, and a side wall part extending along at least either of the first foot part and the second foot part and interposed between either of the foot parts and the coil conductor.

Abstract: The present invention provides a point cloud intra prediction method and device based on weights optimization of neighbors. The invention relates to intra prediction for point cloud attribute compression, by optimizing the weights of the neighboring points on the basis of the density of the point cloud in three directions, i.e. x, y and z directions, and specifically, calculating the optimized weight of each neighboring point by optimizing corresponding coefficients of three coordinate components, i.e. x, y and z coordinate components of distances. The invention can improve the accuracy of intra prediction by means of enhancing the utilization of the overall geometric information of the point cloud, and then transformation, quantification and entropy are carried out on the prediction residuals, such that a better point cloud attribute compression performance is achieved.

Abstract: Disclosed are a method and a device for determining a task-driven pruning module, and a computer readable storage medium. The method includes: obtaining an input task and a task quantity of a neural network to be pruned, and output information of a component module of the neural network to be pruned; determining a task correlation degree of the component module according to the input task, the task quantity and the output information; determining an input information retention degree of the component module according to the task quantity and the output information; determining an importance index value of the component module according to the task correlation degree and the input information retention degree; and determining the pruning module in the neural network to be pruned according to the importance index value.

Abstract: The present disclosure provides a method of positioning vertebra in a CT image, an apparatus, a computer device, and a computer readable storage medium. The method includes: pre-processing vertebra CT image data; inputting the pre-processed vertebra CT image data into a pre-trained neural network to obtain regression results of heat maps of key points corresponding to the pre-processed vertebra CT image data; regressing of 3D heat maps corresponding to the positions of the key points of the vertebra mass center based on the regression results of the heat maps of the key points and the pre-processed vertebra CT image data; serving 3D heat maps corresponding to the positions of the key points of the vertebra mass center as labels, and networked regressing 3D heat map information to position the vertebra. Effects caused by scanning machine difference and scanning noise are avoided, and the vertebra with complex forms is accurately positioned.

Abstract: The present disclosure discloses an ethylene degradation catalyst and a preparation method and a use thereof.

Abstract: A coil component includes a first core having a leg portion, a second core joined to the first core with the leg portion therebetween, and a magnet disposed between the leg portion and the second core. Movement of the magnet in a first direction intersecting a direction in which the first core and the second core face each other is at least restricted by an uneven structure provided on a junction surface between the magnet and at least one of the first core and the second core.

Abstract: The application relates to the technical field of artificial intelligence, and provides a method, device, electronic equipment and storage medium for positioning macular center in fundus images. The method comprises: acquiring a detection result of the fundus image detection model, wherein the detection result includes an optic disc area, and a first detection block and a first confidence score corresponding to the optic disc area, and a macular area, and a second detection block and a second confidence score corresponding to the macular area; calculating a center point coordinate of the optic disc area according to the first detection block, and calculating a center point coordinate of the macular area according to the second detection block; identifying whether the to-be-detected fundus image is a left eye fundus image or a right eye fundus image, and correcting a center point of the macular area using different correction models.

Abstract: The present disclosure provides a gas analysis device and a method for detecting sample gas. The gas analysis device includes: an ion mobility spectrometer including an ion mobility tube, an ion gate, a plurality of electrodes, a suppression grid, and a Faraday plate sequentially disposed in the ion mobility tube, wherein the Faraday plate is configured to receive sample ions discharged from the suppression grid, and the Faraday plate is provided with a through hole; a mass spectrometer; a gate valve disposed between the Faraday plate and an ion inlet of the mass spectrometer; and a controller configured to control an opening or closing of the gate valve to allow the sample ions discharged from the suppression grid to flow into the mass spectrometer through the through hole of the Faraday plate when the gate valve is opened.

Abstract: The present invention relates to the technical field of flue gas denitration catalysts, and discloses a hydrogenated TiO2 denitration catalyst and a preparation method and use thereof. The hydrogenated TiO2 denitration catalyst has a crystal form of anatase form, with oxygen vacancies and surface hydroxyl groups; wherein the hydrogenated TiO2 denitration catalyst contains TiO2, SO3 and P2O5, and based on the total weight of the hydrogenated TiO2 denitration catalyst, the content of TiO2 is 98-99.8% by weight, the content of SO3 is 0.2-1% by weight, and the content of P2O5 is 0.1-0.2% by weight. The hydrogenated TiO2 denitration catalyst has high denitration activity at 300-400° C. and N2 selectivity as high as 85% or more, and can be used in NH3—SCR denitration.

Abstract: Disclosed is an optimization method for constructing a target detection network. The method includes: obtaining high-quality visual media data, low-quality visual media data corresponding to the high-quality visual media data, and a corresponding true label, extracting a first backbone network side output feature generated by a preset prior network for the high-quality visual media data, and extracting a second backbone network side output feature generated by a preset target detection network to be trained for the low-quality visual media data; constructing a feature correlation loss, a salient target position loss and a salient prediction loss based on the first backbone network side output feature, the second backbone network side output feature, and the true label; and optimizing the preset target detection network to be trained based on the feature correlation loss, the salient target position loss, and the salient prediction loss to obtain the target detection network.

Abstract: The instant disclosure is directed to a method for vascularizing a pancreatic islet comprising culturing the pancreatic islet or ?-cells with an endothelial cell comprising an exogenous nucleic acid encoding an ETV2 transcription factor under conditions wherein the endothelial cell expresses the ETV2 transcription factor. The instant disclosure is further directed to a method for making a vascularized ?-cell organoid comprising culturing the pancreatic islet or ?-cells with an endothelial cell comprising an exogenous nucleic acid encoding an ETV2 transcription factor under conditions wherein the endothelial cell expresses the ETV2 transcription factor. Disclosed also are vascularized islets and vascularized ?-cell organoids produced by the methods of the instant disclosure, as well as methods for using the same.

Abstract: The invention discloses a point cloud geometric compression method based on a depth auto-encoder, which comprises the following steps of: (1) point cloud preprocessing: collecting a type of point cloud to be compressed as a training set, and normalizing the training set into a unit circle; (2) point cloud down-sampling: down-sampling the point clouds in the training set so that each point cloud have the same point number m and each point in the point cloud has (x, y, z) three-dimensional coordinates; and adopting a farthest point down-sampling method by randomly selecting a point for the first time and then selecting the point farthest away from the selected point set every time to add into the selected point set until the selected point number meets the requirement; (3) training a compression model: inputting the point cloud sampled in step (2) into a point cloud geometric compression framework based on a depth auto-encoder for training; and (4) geometric compression of the point cloud: applying the trained

Abstract: Embodiments of the present disclosure provide a real-time calibration device, a real-time calibration method and a detection apparatus. The real-time calibration device is in fluid communication with a sample injection pipeline of the apparatus to be calibrated. The real-time calibration device is configured to release a trace amount of calibration agent molecules during a sample injection of the apparatus to be calibrated, so that the trace amount of calibration agent molecules and a sample entering the apparatus to be calibrated are mixed and together enter the apparatus to be calibrated, and information of the sample and the calibration agent is detected by the apparatus to be calibrated, thereby performing a calibration.

Abstract: The present disclosure relates to an artificial intelligence field using a neural network, and publishes a method for confirming a cup-disc ratio based on a neural network, an apparatus, a computer device, and a computer readable storage medium. The method includes: obtaining a retinal image, and detecting an optical disc region in the retinal image to obtain the optical disc region; inputting the optical disc region into a pre-trained neural network to obtain a prediction cup-disc ratio and segment images of an optical cup and an optical disc; computing a cup-disc ratio based on the segment images of the optical cup and the optical disc; and confirming a practical cup-disc ratio based on the prediction cup-disc ratio and the computed cup-disc ratio.

Abstract: A microneedle chip and manufacturing method. The method comprises injecting, into a female mold, a fluid needle liquid, wherein forming cavities matching the shapes of needles of a microneedle chip are provided at the female mold and form a cavity array, injection inlets are provided at a surface of one side of the female mold, and air ejection openings are provided at a surface of another side of the female mold to form an air ejection surface; covering the air ejection surface of the female mold using a breathable film, and during injection, passing a gas through the breathable film so as to retain the liquid inside the forming cavities; curing the fluid needle liquid to form the microneedle chip, and demolding to obtain the same. By employing the air ejection openings and the breathable film, a liquid is retained while ejecting a gas, providing a favorable micro-injection effect.

Abstract: A sampling probe, an automatic sampling device, and a container detection system are provided. The sampling probe includes: a mounting base; a housing mounted on the mounting base, a first accommodation chamber having an opening being defined in the housing, and an exhaust hole in communication with the first accommodation chamber and outside of the housing being formed in the housing; a coupling portion formed on an outer edge of the opening of the first accommodation chamber and formed to be hermetically coupled with an air outlet of a container; and a suction device mounted on the housing and configured to suck gas in the container into the first accommodation chamber through the air outlet. The sampling probe may collect the odor of toxic and harmful gases/hazardous chemicals inside the container at the air outlet of the container, without destroying the overall structure of the container.

Abstract: Provided are a point cloud attribute prediction method and prediction device based on a filter. The method comprises a coding method and a decoding method, and the device comprises a coding device and a decoding device. The method comprises: determining K nearest neighbor points of the current point; determining a filter matrix; and determining an attribute prediction value of the current point according to the filter matrix. Therefore, the compression performance of a point cloud attribute can be improved by means of selecting an appropriate filter.

Abstract: A sampling tube bundle includes a tube bundle body and a joint assembly. The tube bundle body includes a gas sampling tube for transmitting sampling gas; a metal woven layer wrapping an outer circumference of the gas sampling tube; a heating pad comprising a heat tracing cable wrapping an outer circumference of the metal woven layer, for heating the sampling gas in the gas sampling tube; a flame resistant tape wound around an outer circumference of the of the heating pad; a plurality of signal transmission lines circumferentially spaced apart from one another are arranged outside the flame resistant tape; and a sheath located outside the signal transmission line. The joint assembly is arranged on an end of the tube bundle body, for connecting to an analysis device or a sampling device.