Abstract: An ultrahigh-pressure acid-fracturing isodiametric hose assembly, comprising a hose body and a metal joint. The metal joint comprises an inner tube, a first outer tube the inner tube, and a second outer tube. The first outer tube and the second outer tube each is an independent pressing part. An external groove is provided at an outer wall of the inner tube. An end of the first outer tube comprises an internal ridge which matches the external groove for snapping. The terminal of the inner tube comprises a connecting portion. An outer wall of the inner tube comprises a first protrusion, and an inner wall of the first outer tube comprises a second protrusion engaging with the first protrusion. The hose body is clamped between the first protrusion and the second protrusion that are engaged. An inner wall of the second outer tube comprises multiple micro-protrusions.

Abstract: Disclosed is an immersed cabinet, which includes a cabinet body and a heat sink assembly, wherein the heat sink assembly is in sealed connection with the cabinet body and configured to seal an opening of the cabinet body. The cabinet body accommodates a plurality of devices to be cooled, and cooling liquid is put in the cabinet body and used for immersing the plurality of devices to be cooled. The cooling liquid absorbs heat generated by the plurality of devices to be cooled and then is vaporized. The heat sink assembly exchanges heat with the vaporized cooling liquid, so that the vaporized cooling liquid condenses and flows back to the cabinet body for circulation, and the heat sink assembly dissipates the heat into the atmosphere. Therefore, the heat dissipation structure design of the immersed cabinet is effectively simplified.

Abstract: The present application discloses a cerebral perfusion state classification apparatus and method, a device, and a storage medium. The method includes: acquiring, by a transceiving module, cervical blood flow data from an ultrasound data collecting device; determining, by a processor, cerebral perfusion data corresponding to the cervical blood flow data based on the cervical blood flow data and a mapping relationship between the cervical blood flow data and the cerebral perfusion data, and classifying cerebral perfusion states of a plurality of brain regions based on blood perfusion characteristics of the plurality of brain regions in the cerebral perfusion data.

Abstract: Packet recovery mechanisms for wireless networks, which improve end-to-end (e2e) reliability, are provided. First embodiments include packet retransmission between a receiver and a transmitter, wherein, if the transmitter cannot find a lost packet in its transmission buffer, the transmitter sends a First Sequence Number (FSN) report to the receiver to notify the receiver of a sequence number (SN) of an oldest (acknowledged) packet in the buffer. In response, the receiver does not report lost packets whose SN is older than the FSN. Second embodiments involve using a network coding algorithm to recover lost packets, wherein the transmitter sends a control message to the receiver that includes a coded packet to be recovered and information for decoding the coded packet. Other embodiments may be described and/or claimed.

Abstract: An integrated circuit, a control method, and a system are provided, to improve reliability of the integrated circuit. The integrated circuit mainly includes a power supply pin, a configuration pin, a switchable pull-up resistor, and a control unit. The integrated circuit can provide a control signal for a target chip using the configuration pin of the integrated circuit. In the integrated circuit, a first end of the switchable pull-up resistor is connected to the power supply pin, a second end of the switchable pull-up resistor is connected to the configuration pin, and a control end of the switchable pull-up resistor is connected to the control unit. The power supply pin can receive a power supply voltage of the integrated circuit.

Abstract: Embodiments of the disclosure provide systems and methods for detecting a medical condition of a subject. The system includes a communication interface configured to receive a sequence of images acquired from the subject by an image acquisition device and an end-to-end multi-task learning model. The end-to-end multi-task learning model includes an encoder, a Convolutional Recurrent Neural Network (ConvRNN), and at least one of a decoder and a classifier. The system further includes at least one processor configured to extract feature maps from the images using the encoder, capture contextual information between adjacent images in the sequence using the ConvRNN, and detect medical condition of the subject using the classifier based on the extracted feature maps of the image slices and the contextual information or segment each image slice using the decoder to obtain a region of interest indicative of the medical condition based on the extracted feature maps.

Abstract: Provided are a CT scanning method and system, an electronic device, and a computer-readable storage medium. The method includes: determining a first coordinate of a mark point of a part to be imaged in a dual-camera coordinate system; converting the first coordinate into a second coordinate of the mark point in a CT coordinate system according to coordinate system transformation parameters; generating first locating information according to the second coordinate to drive a scanning table to move to a first location designated by the first locating information; obtaining projection images of the part to be scanned; determining second locating information and scanning information of the part to be scanned according to the projection images; and driving the scanning table to move to a second location designated by the second locating information according to the second locating information and performing CT scanning according to the scanning information.

Abstract: The present application discloses a cerebral perfusion state classification apparatus and method, a device, and a storage medium. The method includes: acquiring, by a transceiving module, cervical blood flow data from an ultrasound data collecting device; determining, by a processor, cerebral perfusion data corresponding to the cervical blood flow data based on the cervical blood flow data and a mapping relationship between the cervical blood flow data and the cerebral perfusion data, and classifying cerebral perfusion states of a plurality of brain regions based on blood perfusion characteristics of the plurality of brain regions in the cerebral perfusion data.

Abstract: The present disclosure discloses a cerebral perfusion state classification apparatus, method and device, and a model training apparatus. In the apparatus, a transceiver module is used for receiving physiological feature data from different data collection devices; and a processor is used for extracting physiological features from the physiological feature data; inputting the physiological features into a random forest model to cause a plurality of decision-making trees in the random forest model to predict a cerebral perfusion state type corresponding to the physiological features; and classifying a cerebral perfusion state based on the cerebral perfusion state type corresponding to the physiological features.

Abstract: A method and apparatus with neural network optimization are provided. A method is performed by a device storing a target network block and processing hardware that performs optimizing for the target network block, the method includes generating, by the processing hardware, an extended network block of the target network block by increasing, a number of channels of a target operation branch in the target network block to a determined number of channels, wherein the target network block includes operation branches that include the target operation branch, and wherein each operation branch includes at least one respective channel, determining importance measures of the respective operation branches, including the target operation branch with the increased number of channels, in the extended network block, and clipping a channel of the target operation branch in the extended network block, the clipping is performed according to the importance measures of the respective operation branches.

Abstract: The present disclosure discloses a cerebral perfusion state classification apparatus, method and device, and a model training apparatus. In the apparatus, a transceiver module is used for receiving physiological feature data from different data collection devices; and a processor is used for extracting physiological features from the physiological feature data; inputting the physiological features into a random forest model to cause a plurality of decision-making trees in the random forest model to predict a cerebral perfusion state type corresponding to the physiological features; and classifying a cerebral perfusion state based on the cerebral perfusion state type corresponding to the physiological features.

Abstract: A method and device for suppressing range ambiguity and a computer readable storage medium are provided. The method includes: determining a pulse timing relationship of a transmission signal; determining orthogonal nonlinear frequency modulation signals; modulating the transmission signal by using the orthogonal nonlinear frequency modulation signals; transmitting the modulated transmission signal according to the pulse timing relationship, and determining echo data of the modulated transmission signal; and generating an image according to a polarization scattering matrix for the echo data of the modulated transmission signal.

Abstract: An integrated circuit, a control method, and a system are provided, to improve reliability of the integrated circuit. The integrated circuit mainly includes a power supply pin (P1), a configuration pin (P4, P5), a switchable pull-up resistor (KR1, KR2), and a control unit (2011). The integrated circuit can provide a control signal for a target chip (202) by using the configuration pin (P4, P5) of the integrated circuit. In the integrated circuit, a first end of the switchable pull-up resistor (KR1, KR2) is connected to the power supply pin (P1), a second end of the switchable pull-up resistor (KR1, KR2) is connected to the configuration pin (P4, P5), and a control end of the switchable pull-up resistor (KR1, KR2) is connected to the control unit (2011). The power supply pin (P1) can receive a power supply voltage of the integrated circuit.

Abstract: A method for concentrating rubber emulsion and a product prepared by the method are provided, the method includes: a concentrated latex is obtained by separating a superabsorbent resin added in advance into a rubber emulsion with a solid content of 0.01-70% after stirring and concentrating the resin-added rubber emulsion. The method requires simple equipment and consumes less energy, and the prepared polymer emulsion has a solid content up to 76%; the superabsorbent resin adopted herein is reusable after drying, which therefore effectively reduces the production cost; natural latex concentrated by the method has rather high yields of dry rubber and little wastewater production; products prepared from the concentrated natural latex have excellent mechanical property, aging resistance and adhesive property; and concentrating natural latex according to this method does not require advance agglomeration, which reduces the production procedures and improves the production efficiency significantly.

Abstract: The present disclosure relates to a training method and a training system for training a learning network for medical image analysis. The training method includes: acquiring an original training data set for a learning network with a predetermined structure; performing, by a processor, a pre-training on the learning network using the original training data set to obtain a pre-trained learning network; evaluating, by the processor, the pre-trained learning network to determine whether the pre-trained learning network has an evaluation defect; when the pre-trained learning network has the evaluation defect, performing, by the processor, a data augmentation on the original training data set for the existing evaluation defect; and performing, by the processor, a refined training on the pre-trained learning network using a data augmented training data set.

Abstract: A method for concentrating rubber emulsion and a product prepared by the method are provided, the method includes: a concentrated latex is obtained by separating a superabsorbent resin added in advance into a rubber emulsion with a solid content of 0.01-70% after stirring and concentrating the resin-added rubber emulsion. The method requires simple equipment and consumes less energy, and the prepared polymer emulsion has a solid content up to 76%; the superabsorbent resin adopted herein is reusable after drying, which therefore effectively reduces the production cost; natural latex concentrated by the method has rather high yields of dry rubber and little wastewater production; products prepared from the concentrated natural latex have excellent mechanical property, aging resistance and adhesive property; and concentrating natural latex according to this method does not require advance agglomeration, which reduces the production procedures and improves the production efficiency significantly.

Abstract: The present disclosure relates to a medical image analysis method, a medical image analysis device, and a computer-readable storage medium. The medical image analysis method includes receiving a medical image acquired by a medical imaging device; determining a navigation trajectory by performing navigation processing on the medical image based on an analysis requirement, the analysis requirement indicating a disease to be analyzed; extracting an image block set along the navigation trajectory; extracting image features using a first learning network based on the image block set; and determining an analysis result using a second learning network based on the image features and the navigation trajectory.

Abstract: The present disclosure relates to a lignite transient dehydration upgrading and temperature and pressure instant generation device system. Materials are added by a feeding device above the steam dehydration system and enter a feeding area, at the moment, a sealing valve is opened, an internal material platform is pushed forwards in a rotary mode, wet materials enter a dehydration area, and then the sealing valve is closed after dry materials enter. Saturated steam is added into the device by the steam generation system, then the device is adjusted to be in a high-temperature and high-pressure state by the electric control system, and the pressure is continuously stabilized for a certain period of time. The sealing valve is then opened, the dry materials enter a discharging area and then are discharged by a conveying belt, while new wet materials enter the dehydration area accordingly to begin the next round of dehydration.

Abstract: A detection report data generation method including acquiring event type information of an electrocardiogram event corresponding to electrocardiogram event data, wherein the event data has one or more pieces of event type information; screening the event data according to signal quality evaluation indexes so as to obtain report conclusion data and report entry data; carrying out quality assessment on an event segment included in the event data according to the signal quality evaluation indexes, and determining a pre-selected sample segment according to a quality assessment result; determining position information of an event heart beat in the pre-selected sample segment, and determining segment interception parameters; carrying out interception processing on the pre-selected sample segment according to the segment interception parameters so as to obtain a typical data segment; generating report graphic data according to the typical data segment; and outputting the entry data, the graphic data and the conclusi

Abstract: The present disclosure relates to a medical image analysis method, a medical image analysis device, and a computer-readable storage medium. The medical image analysis method includes receiving a medical image acquired by a medical imaging device; determining a navigation trajectory by performing navigation processing on the medical image based on an analysis requirement, the analysis requirement indicating a disease to be analyzed; extracting an image block set along the navigation trajectory; extracting image features using a first learning network based on the image block set; and determining an analysis result using a second learning network based on the image features and the navigation trajectory.