Abstract: A coenzyme Q10 slow-release drug includes an isolation layer and a drug layer, where the drug layer is composed of coenzyme Q10 and a pharmaceutically acceptable carrier; the isolation layer is composed of a degradable gel; a diameter of the drug layer is not larger than that of the isolation layer. The coenzyme Q10 slow-release drug is prepared as follows. (S1) The degradable gel is laid on a mold for casting into a film to form the isolation layer. (S2) Coenzyme Q10 and the pharmaceutically acceptable carrier are mixed and laid on the mold in step (S1) for casting to form the drug layer on the isolation layer. (S3) Steps (S1) and (S2) are repeated, and then edges of adjacent controlled-release layers are bonded to obtain the coenzyme Q10 slow-release drug.

Abstract: The present disclosure relates to a method for predicting an amount of water-sealed gas in a high-sulfur water-bearing gas reservoir. The method solves the problem that no method has yet been proposed for predicting the amount of water-sealed gas in a high-sulfur water-bearing gas reservoir. According to the technical solution, the method includes: considering that the volume of the gas reservoir does not change during the production of the constant-volume gas reservoir, deriving, based on a material balance method, a material balance equation of the high-sulfur water-bearing gas reservoir in consideration of water-sealed gas and water-soluble gas, solving and drawing a chart of water-sealed gas in the high-sulfur water-bearing gas reservoir by an iterative algorithm, obtaining a recovery factor of the high-sulfur water-bearing gas reservoir in consideration of water-sealed gas and water-soluble gas, and further obtaining the amount of water-seal gas in the high-sulfur water-bearing gas reservoir.

Abstract: The present application provides a demultiplexing circuit, a control method thereof and a display device, which include at least one demultiplexing module and a switch control module. A compensation unit of each demultiplexing unit in the demultiplexing module is coupled to a voltage level of an output end of a data writing transistor according to a clock signal received by a control end of the data writing transistor. The output end of each switch control unit of the switch control module is electrically connected to the control end of the data writing transistor included in a demultiplexing unit.

Abstract: A coenzyme Q10 slow-release drug includes an isolation layer and a drug layer, where the drug layer is composed of coenzyme Q10 and a pharmaceutically acceptable carrier; the isolation layer is composed of a degradable gel; a diameter of the drug layer is not larger than that of the isolation layer. The coenzyme Q10 slow-release drug is prepared as follows. (S1) The degradable gel is laid on a mold for casting into a film to form the isolation layer. (S2) Coenzyme Q10 and the pharmaceutically acceptable carrier are mixed and laid on the mold in step (S1) for casting to form the drug layer on the isolation layer. (S3) Steps (S1) and (S2) are repeated, and then edges of adjacent controlled-release layers are bonded to obtain the coenzyme Q10 slow-release drug.

Abstract: A method and system for intelligent plan optimization. The method may include: obtaining a sample scan image, one or more sample contour images, and sample dose data by resampling a scan image, a contour image, and dose data at a same resolution; obtaining a weighted image by the one or more sample contour images; obtaining a sample weighted image by performing a dimensionality reduction on the weighted image; obtaining a trained regression model by performing a regression training on an initial regression model based on the sample scan image, the contour image of the sample target region, the sample weighted image, and the sample dose data corresponding to the sample scan image; and obtaining a dose prediction result by inputting a to-be-tested scan image, a to-be-tested contour image of the target region, and a to-be-tested weighted image after the dimensionality reduction into the trained regression model.

Abstract: A backlight module and a display panel are provided. The display panel includes a display panel main body and a backlight module. The backlight module includes a light guide, a first reflector, and a light source. By arranging the light source in a receiving cavity of the light guide, a width of a lamp socket of the backlight module is reduced, and a light effect of the lamp socket of the backlight module is improved.

Abstract: Provided is a device for spraying an ammoniacal gas in an automatically-adjustable manner based on a flow rate

Abstract: Systems and methods for controlling a vertical pumping unit are provided. The method includes a self-learning phase and a running phase, wherein the self-learning phase includes obtaining a self-learning result and the running phase includes controlling a motor of the vertical pumping unit to run according to the self-learning result and preset running parameters. The method enables the vertical pumping unit to adjust running parameters of the running phase according to the self-learning results, avoid the accumulation of errors effectively so that changes in stroke length and stroke frequency caused by the motor V-belt, load belt extension and retraction and other elastic links are limited to a minimum range so as to ensure the running accuracy of the vertical pumping unit.

Abstract: Examples provide a system and method for retraining a machine learning (ML) algorithm associated with a trained model using root cause pattern recognition. The system analyzes the results of parsing unstructured data and identifies a root cause pattern causing the trained model to underperform when parsing data including the identified pattern. Examples of data including the pattern are created for use in retraining the model to correctly detect and parse data following the identified pattern. Once retrained, the model is able to parse unstructured data, including data having the identified pattern, in accordance with expected performance metrics. The system automatically identifies parsing errors, identifies the root cause patterns for these errors and retrains the models to correctly handle those patterns for more accurate and efficient handing of unstructured data by trained models.

Abstract: A method and a system for analyzing a transient current of a non-polar liquid, and an apparatus are disclosed. The method includes: measuring a transient current of a to-be-detected device to obtain a transient current reference curve; determining experimental parameters of a first influencing factor in the to-be-detected device according to the transient current reference curve and preset equations, and measuring experimental parameters of a second influencing factor in the device; constructing a transient current reference model according to the experimental parameters of the first and second influencing factors and a preset current model; adjusting parameters of the first and/or second influencing factor in the transient current reference model to obtain a plurality of transient current models; and calculating corresponding transient current change data according to the transient current models to construct and output a plurality of transient current curves.

Abstract: Examples provide a system and method for retraining a machine learning (ML) algorithm associated with a trained model using root cause pattern recognition. The system analyzes the results of parsing unstructured data and identifies a root cause pattern causing the trained model to underperform when parsing data including the identified pattern. Examples of data including the pattern are created for use in retraining the model to correctly detect and parse data following the identified pattern. Once retrained, the model is able to parse unstructured data, including data having the identified pattern, in accordance with expected performance metrics. The system automatically identifies parsing errors, identifies the root cause patterns for these errors and retrains the models to correctly handle those patterns for more accurate and efficient handing of unstructured data by trained models.

Abstract: Disclosed is a computer implemented method, system and computer readable medium for performing blockchain-based identity management for a supply chain of a computerised network. In one aspect, the method includes receiving, by a computerised device of a party, an identity issuing transaction initiated by a computerised component or service being in the supply chain, the identity issuing transaction being indicative of a name of the computerised component or service, an identity issuing request message, and a first random number obtained from a distributed database, wherein the identity issuing transaction is initiated by the computerised component or service in response to determining the party is an authoritative party recorded in the blockchain and permitted to issue an identity, invoking a first smart contract, and executing an identity issuance logic of the first smart contract.

Abstract: A rotation bracket includes an L-shaped connecting rod, a rotation mechanism, and a stand base. The L-shaped connecting rod includes a vertical rod and a horizontal rod. The vertical rod is configured to connect to a communications device. The horizontal rod is fastened to the rotation mechanism, and the horizontal rod is a rotatable rod. The rotation mechanism is fastened to a top of the stand base, and the rotation mechanism is configured to drive the L-shaped connecting rod to rotate in a horizontal plane. The stand base is configured to fixedly connect to an inner surface of a wall or to a ground.

Abstract: Systems, apparatuses and methods may provide technology for managing a runtime computing environment having tiered object memory placement that assigns a hotness score to an object having an object type based on an invocation count of objects referenced by a hot method, allocates a newly-created object to one of a hot object heap, said hot object heap assigned to store hot objects in a first memory tier, or a cold object heap, said cold object heap assigned to store cold objects in a second memory tier, based on the hotness score associated with the object type for the newly-created object, and migrates a plurality of objects between the hot object heap and the cold object heap based on a hotness score associated with each object. The technology may also operate the object migration in an execution thread independent of an execution thread for the object allocation.

Abstract: Systems and methods for controlling a vertical pumping unit are provided. The method includes a self-learning phase and a running phase, wherein the self-learning phase includes obtaining a self-learning result and the running phase includes controlling a motor of the vertical pumping unit to run according to the self-learning result and preset running parameters. The method enables the vertical pumping unit to adjust running parameters of the running phase according to the self-learning results, avoid the accumulation of errors effectively so that changes in stroke length and stroke frequency caused by the motor V-belt, load belt extension and retraction and other elastic links are limited to a minimum range so as to ensure the running accuracy of the vertical pumping unit.

Abstract: Examples provide a system and method for retraining a machine learning (ML) algorithm associated with a trained model using root cause pattern recognition. The system analyzes the results of parsing unstructured data and identifies a root cause pattern causing the trained model to underperform when parsing data including the identified pattern. Examples of data including the pattern are created for use in retraining the model to correctly detect and parse data following the identified pattern. Once retrained, the model is able to parse unstructured data, including data having the identified pattern, in accordance with expected performance metrics. The system automatically identifies parsing errors, identifies the root cause patterns for these errors and retrains the models to correctly handle those patterns for more accurate and efficient handing of unstructured data by trained models.

Abstract: Embodiments of the present application disclose a coupling device and an all-terrain vehicle. The coupling device includes: a first coupling member including a first tube portion and a first solid portion coupled to the first tube portion; and a second coupling member including a second tube portion and a second solid portion coupled to the second tube portion. The second solid portion is detachably coupled to the first solid portion. In the coupling device of embodiments of the present application, the first coupling member includes the first tube portion, and the second coupling member includes the second tube portion, thereby greatly reducing the weight of the coupling device and transportation costs of the coupling device.

Abstract: An all-terrain vehicle and a gear shifting device for an all-terrain vehicle are disclosed. The all-terrain vehicle includes: a motor; a controller electrically coupled to the motor; and an electronic shifter electrically coupled to the controller. Thus, by adopting the electronic shifter, the unstable and unsmooth problem associated with purely mechanical shifting devices can be addressed, and the problems of small operation space and operation inconvenience for the drivers can be solved.

Abstract: In some examples, feature and context based search result generation may include identifying, based on analysis of a query feature associated with a query context of a query, and an entity feature associated with an entity context of each entity of a plurality of entities, a reduced number of entities that match the query. Based on analysis of a further query feature and a further entity feature, further matching analysis of the query to the reduced number of entities may be performed. The query may be linked by a linking model to an entity of the reduced number of entities to generate a query and entity pair. Selection of an entity may be received, and a linked plurality of queries and entities may be searched. In this regard, search results may be generated and include a set of queries that is associated with the selected entity.

Abstract: A rotation bracket includes an L-shaped connecting rod, a rotation mechanism, and a stand base. The L-shaped connecting rod includes a vertical rod and a horizontal rod. The vertical rod is configured to connect to a communications device. The horizontal rod is fastened to the rotation mechanism, and the horizontal rod is a rotatable rod. The rotation mechanism is fastened to a top of the stand base, and the rotation mechanism is configured to drive the L-shaped connecting rod to rotate in a horizontal plane. The stand base is configured to fixedly connect to an inner surface of a wall or to a ground.