Abstract: A secondary battery is disclosed. The secondary battery includes a positive electrode plate, a negative electrode plate, a separator, and an electrolyte solution. The positive electrode plate includes a positive active material. The positive active material includes a core and a coating. A manganese content of the core is greater than or equal to 25% based on a mass of the core. The coating overlays a surface of the core and contains one or more of an oxide, hydroxide, or oxyacid salt of element X. The element X is one or more selected from Al, B, or P. A mass ratio of the coating to the core is 1:(5 to 100), and optionally 1:(16 to 100). The electrolyte solution contains a first solvent. The first solvent is one or more selected from a fluorocarbonate ester, a fluorocarboxylate ester, a fluorosulfone, a fluoroether, or a fluorobenzene.

Abstract: Provided are a sound gathering device for voiceprint monitoring and a preparation method. The sound gathering device is a cone structure and includes a front end portion (1) and a rear end portion (2), the front end portion (1) is trumpet-shaped, an inner wall surface of the front end portion (1) is present a pattern array of a microstructure (3), and the microstructure (3) presenting the pattern array is formed through laser etching. A sound wave frequency monitored by the sound gathering device is 50 Hz˜10 kHz, and a sound wave enters the sound gathering device from an entrance of the front end portion (1), is reflected through the pattern array of the microstructure (3) on the inner wall surface of the front end portion (1), and is transmitted from an exit of the rear end portion (2), and a sound pressure of the exit of the rear end portion (2) is 4 times˜8 times a sound pressure of the entrance of the front end portion (1).

Abstract: The invention relates to a method for improving shunting route setting of a centralized traffic control system, a device and a medium. The method comprises the following steps: S1, acquiring a shunting operation plan from an interface of a SMIS and generating a shunting route sequence, by a centralized traffic control system; S2, adding an operation direction, a location identifier of a shunter, a current control mode of the shunter and a description of a next route based on an original shunter number of the centralized traffic control system; S3, configuring a manual setting mode and an automatic triggering mode for shunting route setting; S4, adding identifiers of the manual setting mode and the automatic triggering mode to shunter number display; S5, in the manual setting mode, adding a shunting plan constraint state and a free setting state to a shunting route setting logic of the centralized traffic control system; and the like.

Abstract: A preparation method of a polymer-derived high-temperature ceramic thin film sensor is provided. Specifically, a sensitive layer precursor layer is prepared by spraying a sensitive layer precursor liquid on an alumina substrate, and the sensitive layer precursor liquid is obtained by mixing precursor liquid with conductive powder. A protective layer precursor liquid is prepared by spraying protective layer precursor liquid on the sensitive layer precursor layer, and the protective layer precursor liquid is obtained by mixing TiB2 nano-powder, insulating powder and the precursor liquid. The protective layer precursor layer, a solder and the sensitive layer precursor layer are simultaneously pyrolyzed by a one-time pyrolysis process, and thus a protective layer, the solder joints and the sensitive layer are obtained simultaneously. Thus, there is no need to pyrolyze the sensitive layer first, saving the time for pyrolyzing the sensitive layer.

Abstract: A preparation method of a polymer-derived high-temperature ceramic thin film sensor is provided. Specifically, a sensitive layer precursor layer is prepared by spraying a sensitive layer precursor liquid on an alumina substrate, and the sensitive layer precursor liquid is obtained by mixing precursor liquid with conductive powder. A protective layer precursor liquid is prepared by spraying protective layer precursor liquid on the sensitive layer precursor layer, and the protective layer precursor liquid is obtained by mixing TiB2 nano-powder, insulating powder and the precursor liquid. The protective layer precursor layer, a solder and the sensitive layer precursor layer are simultaneously pyrolyzed by a one-time pyrolysis process, and thus a protective layer, the solder joints and the sensitive layer are obtained simultaneously. Thus, there is no need to pyrolyze the sensitive layer first, saving the time for pyrolyzing the sensitive layer.

Abstract: A system and method for implementing slot-relation extraction for a task-oriented dialogue system that includes implementing dialogue intent classification machine learning models that predict a category of dialogue of a single utterance based on an input of utterance data relating to the single utterance, wherein the category of dialogue informs a selection of slot-filling machine learning models; implementing the slot-filling machine learning models that predict slot classification labels for each of a plurality of slots within the utterance based on the input of the utterance data; implementing a slot relation extraction machine learning model that predicts semantic relationship classifications between two or more distinct slots of tokens of the utterance; and generating a response to the single utterance or performing actions in response to the single utterance based on the semantic relationship classifications between the distinct pairings of the two or more distinct slots of the single utterance.

Abstract: A system and method for implementing slot-relation extraction for a task-oriented dialogue system that includes implementing dialogue intent classification machine learning models that predict a category of dialogue of a single utterance based on an input of utterance data relating to the single utterance, wherein the category of dialogue informs a selection of slot-filling machine learning models; implementing the slot-filling machine learning models that predict slot classification labels for each of a plurality of slots within the utterance based on the input of the utterance data; implementing a slot relation extraction machine learning model that predicts semantic relationship classifications between two or more distinct slots of tokens of the utterance; and generating a response to the single utterance or performing actions in response to the single utterance based on the semantic relationship classifications between the distinct pairings of the two or more distinct slots of the single utterance.

Abstract: A system and method for implementing slot-relation extraction for a task-oriented dialogue system that includes implementing dialogue intent classification machine learning models that predict a category of dialogue of a single utterance based on an input of utterance data relating to the single utterance, wherein the category of dialogue informs a selection of slot-filling machine learning models; implementing the slot-filling machine learning models that predict slot classification labels for each of a plurality of slots within the utterance based on the input of the utterance data; implementing a slot relation extraction machine learning model that predicts semantic relationship classifications between two or more distinct slots of tokens of the utterance; and generating a response to the single utterance or performing actions in response to the single utterance based on the semantic relationship classifications between the distinct pairings of the two or more distinct slots of the single utterance.

Abstract: A system and method for implementing slot-relation extraction for a task-oriented dialogue system that includes implementing dialogue intent classification machine learning models that predict a category of dialogue of a single utterance based on an input of utterance data relating to the single utterance, wherein the category of dialogue informs a selection of slot-filling machine learning models; implementing the slot-filling machine learning models that predict slot classification labels for each of a plurality of slots within the utterance based on the input of the utterance data; implementing a slot relation extraction machine learning model that predicts semantic relationship classifications between two or more distinct slots of tokens of the utterance; and generating a response to the single utterance or performing actions in response to the single utterance based on the semantic relationship classifications between the distinct pairings of the two or more distinct slots of the single utterance.

Abstract: The invention belongs to the technical field of preparation of a ceramsite catalyst and discloses a ceramsite catalyst containing metal oxide particles and a preparation method and application thereof. The preparation method including the following specific steps of: dissolving a metal salt with an ozone catalytic activity in water to obtain a metal salt solution; mixing the metal salt solution with a ceramsite raw material to prepare a ceramsite embryoid body; and sintering the ceramsite embryoid body at a high temperature to obtain the ceramsite catalyst containing metal oxide particles. The ceramsite catalyst containing metal oxide particles of the invention can be repeatedly used, so that secondary pollution is reduced; and with the same ozone input quantity, by adding the ceramsite catalyst containing metal oxide particles of the present invention, the efficiency of water treatment through ozone oxidization can be increased by 41.35%.

Abstract: A software deployment method creates and provides an installation parameter file for each computer to be deployed according to a software deployment task. The installation parameter file of each computer to be deployed is used to guide a network installation of software on the computer. A corresponding software deployment system, a software deployment server, and a software deployment user server are also provided. The installation parameter files are generated collectively according to the software deployment tasks, so that the computer equipment is guided by the installation parameter file to install the software automatically. Therefore, the software deployment on the computers in batches is more convenient. Moreover, as the installation parameter file corresponds to each computer to be deployed, the software type and the parameter configuration of each computer to be deployed can be adjusted flexibly, which facilitates the customization of the software.

Abstract: A software deployment method creates and provides an installation parameter file for each computer to be deployed according to a software deployment task. The installation parameter file of each computer to be deployed is used to guide a network installation of software on the computer. A corresponding software deployment system, a software deployment server, and a software deployment user server are also provided. The installation parameter files are generated collectively according to the software deployment tasks, so that the computer equipment is guided by the installation parameter file to install the software automatically. Therefore, the software deployment on the computers in batches is more convenient. Moreover, as the installation parameter file corresponds to each computer to be deployed, the software type and the parameter configuration of each computer to be deployed can be adjusted flexibly, which facilitates the customization of the software.