Abstract: The disclosure belongs to the field of battery technology and specifically relates to a battery cover plate and a secondary battery including: a cover plate body provided with an electrode terminal hole; and an electrode terminal assembly including an electrode terminal body and a limiting piece. The electrode terminal body is inserted into the electrode terminal hole. The limiting piece is engaged with the electrode terminal body in a thickness direction of the electrode terminal body to fix the limiting piece made of a first material. A portion of the electrode terminal body engaged with the limiting piece is made of a first conductive material. A hardness of the first material is greater than a hardness of the first conductive material. In the disclosure, the limiting piece made of a high-hardness material is engaged in the thickness direction of the electrode terminal body.

Abstract: In implementations of systems and procedures for a service provider system, a computing device implements predictive recommendation generation. A registration component is employed to register a specific interaction sequence defining an order of user interactions to be performed by a single user during a session on a platform. The specific interaction sequence is predicted to proceed to a request for a recommendation result by the single user. Additionally, an interaction monitor is configured to monitor, in real-time, interaction sequences of a plurality of users. In response to detecting the specific interaction sequence for a user of the plurality of users, the interaction monitor triggers, in real-time, pre-calculation of the recommendation result for the user, and a cache stores the pre-calculated recommendation result.

Abstract: A cover plate assembly, a battery cell, and a battery pack are provided. The cover plate assembly includes a cover plate body provided with a through hole; an outer conductive member disposed on a side of the cover plate body away from an electrode assembly and including a first metal layer, a second metal layer, and a third metal layer disposed between the first metal layer and the second metal layer; and an electrode lead-out member passing through the through hole and electrically connected to the outer conductive member. The third metal layer is respectively connected to the first metal layer and the second metal layer to form a first composite layer and a second composite layer. The first composite layer includes a first metal and a third metal. The second composite layer includes a second metal and the third metal.

Abstract: A secondary battery, a battery assembly, and an electronic apparatus is provided. The secondary battery includes a housing, an electrode terminal, an electrode assembly, and a current collecting member. The housing includes an end wall and a side wall. The end wall includes a terminal hole and an explosion-proof notch. An area surrounded by the explosion-proof notch on the end wall is an explosion-proof area. The electrode terminal is insulated, sealed, and fixed to the end wall. The electrode assembly is disposed in the housing, and a side of the electrode assembly facing the end wall includes a first electrode tab. The current collecting member includes a main body portion connected to the first electrode tab and a terminal connecting portion connected to the electrode terminal. The main body portion includes a deformable portion which is adapted to maintain the connection between the electrode terminal and the main body portion.

Abstract: The present disclosure relates to a method for configuring a priority level, a cloud platform, a system, a computing device, and a medium. The method for configuring a priority level for data on a cloud platform comprises determining the data type of received data; determining, according to the data type, a priority level specification used for describing a priority level of the received data; and calculating the priority level of the received data on the basis of the priority level specification of the received data.

Abstract: The present disclosure provides a direct current (DC) transformer error detection apparatus for a pulsating harmonic signal, including a DC and pulsating harmonic current output module and an external detected input module, where the DC and pulsating harmonic current output module outputs a DC and a DC superimposed pulsating harmonic current to an internal sampling circuit and a self-calibrated standard resistor array; and the internal sampling circuit converts the input DC and the input DC superimposed pulsating harmonic current into a voltage signal, and sends the voltage signal to an analog-to-digital (AD) sampling and measurement component through a front-end conditioning circuit and a detected input channel. The DC transformer error detection apparatus can complete self-calibration for measurement of the DC and the pulsating harmonic signal on a test site.

Abstract: The present disclosure provides a language model based writing aid method, apparatus and system. The method includes: a server acquiring original text, where the original text may be writing text already generated and/or user input text; the server inputting the original text into a language model to generate a preset number of pieces of writing text, where the writing text and the original text have a correlation; the server sending the preset number of pieces of writing text to a frontend interface. The method of the present disclosure enables a computer to aide a user in text creating so that intelligence for writing aid is improved.

Abstract: The present disclosure provides a direct current (DC) transformer error detection apparatus for a pulsating harmonic signal, including a DC and pulsating harmonic current output module and an external detected input module, where the DC and pulsating harmonic current output module outputs a DC and a DC superimposed pulsating harmonic current to an internal sampling circuit and a self-calibrated standard resistor array; and the internal sampling circuit converts the input DC and the input DC superimposed pulsating harmonic current into a voltage signal, and sends the voltage signal to an analog-to-digital (AD) sampling and measurement component through a front-end conditioning circuit and a detected input channel. The DC transformer error detection apparatus can complete self-calibration for measurement of the DC and the pulsating harmonic signal on a test site.

Abstract: The present invention provides a supported metal catalyst with synergistic sites, a preparation method therefor and an application thereof. The preparation method of this catalyst is to utilize the unsaturated cubane-like structure, M cation with catalytic activity is introduced into the cluster core unit. By using the vertex vacancy as the capturing center, and adjusting the impregnation temperature to maximize the loading of the cluster precursor, as well as depending on the electrostatic adsorption of the support and the confinement of the cluster structural unit, the number of S vacancies and the distance between S vacancies and Miso sites are effectively controlled through liquid phase reduction and atmosphere treatment at room temperature to obtain supported X3MSx/Al2O3 catalyst with Miso-Vs synergistic sites.

Abstract: Various embodiments include a method for deploying field device into an Internet of Things (IoT). The method may include: acquiring information from a field device using an edge device; transmitting the acquired information to a cloud platform; wherein the information comprises data and an industrial IoT model; converting the industrial IoT model into a graph; performing similarity analysis based on the graph; classifying the industrial IoT model based on the similarity analysis; generating a first industrial IoT model comprising a type or an example; performing data mapping on the first industrial IoT model; and operating the field device as part of the IoT.

Abstract: Various embodiments of the teachings herein include a method for generating a virtual Internet-of-things device on the basis of an Internet-of-things model. The method may include: obtaining a first number of Internet-of-things models for an Internet-of-things solution; subjecting a variable in the first number of Internet-of-things models to variable attribute expansion to add an extended variable attribute to the variable, wherein the variable subjected to variable attribute expansion is capable of data simulation; configuring variable link relations and variable link processing rules for the extended Internet-of-things models to obtain an Internet-of-things model configuration file; and obtaining a second number of virtual Internet-of-things devices on the basis of a virtual physical network device architecture by using the Internet-of-things model configuration file.

Abstract: Various embodiments described herein include an application program development and deployment method comprising: acquiring, from a code template library, a first code template matching a code structure of an application program to be developed; creating a template instance based on the first code template; filling a custom code input by a developer into the template instance to obtain a source program code matching said application program; compiling the source program code to obtain a target program code; acquiring a target operating environment mirror matching the target program code from an environment mirror library, wherein at least one operating environment mirror is stored in the environment mirror library, and different operating environment mirrors correspond to different operating environments; and deploying the target program code and the target operating environment mirror onto a target cloud platform.

Abstract: Various embodiments include methods for determining a resource configuration of a cloud service system using a system simulation tool with a model library. This may include: obtaining a model required for each service; obtaining a resource limit setting of each required model; creating a service workflow among the models to obtain a system simulation model, indicating the interaction workflow among the models and the sequence of model execution in a single service; using training data to train a service performance model of each service, wherein the training data comprises test data collected from the cloud service system in a testing environment, and the service performance model defines a resource consumption of a single request running on a service in the system simulation model; performing system simulation with a given resource configuration set and the resource limit settings, to obtain a system performance KPI; and determining a resource configuration with the best KPI.

Abstract: A field data transmission method comprises: a cloud platform determining at least one first device operation index be obtained via data analysis. For each first device operation index, the cloud platform generates control information for the first device operation index. The control information is used to determine a primary edge controller from among at least one edge controller, wherein the primary edge controller is used to send first field data to the cloud platform, the first field data is used for data analysis by the cloud platform to obtain the first device operation index, and the first field data is obtained by the primary edge controller preprocessing second field data. The cloud platform sends each piece of control information to each edge controller, respectively. The cloud platform receives first field data from each primary edge controller, respectively.

Abstract: Various embodiments include methods for determining a resource configuration of a cloud service system using a system simulation tool with a model library. This may include: obtaining a model required for each service; obtaining a resource limit setting of each required model; creating a service workflow among the models to obtain a system simulation model, indicating the interaction workflow among the models and the sequence of model execution in a single service; using training data to train a service performance model of each service, wherein the training data comprises test data collected from the cloud service system in a testing environment, and the service performance model defines a resource consumption of a single request running on a service in the system simulation model; performing system simulation with a given resource configuration set and the resource limit settings, to obtain a system performance KPI; and determining a resource configuration with the best KPI.

Abstract: Various embodiments include a method for deploying field device into an Internet of Things (IoT). The method may include: acquiring information from a field device using an edge device; transmitting the acquired information to a cloud platform; wherein the information comprises data and an industrial IoT model; converting the industrial IoT model into a graph; performing similarity analysis based on the graph; classifying the industrial IoT model based on the similarity analysis; generating a first industrial IoT model comprising a type or an example; performing data mapping on the first industrial IoT model; and operating the field device as part of the IoT.

Abstract: Various embodiments of the teachings herein include a method for generating a virtual Internet-of-things device on the basis of an Internet-of-things model. The method may include: obtaining a first number of Internet-of-things models for an Internet-of-things solution; subjecting a variable in the first number of Internet-of-things models to variable attribute expansion to add an extended variable attribute to the variable, wherein the variable subjected to variable attribute expansion is capable of data simulation; configuring variable link relations and variable link processing rules for the extended Internet-of-things models to obtain an Internet-of-things model configuration file; and obtaining a second number of virtual Internet-of-things devices on the basis of a virtual physical network device architecture by using the Internet-of-things model configuration file.

Abstract: Various embodiments described herein include an application program development and deployment method comprising: acquiring, from a code template library, a first code template matching a code structure of an application program to be developed; creating a template instance based on the first code template; filling a custom code input by a developer into the template instance to obtain a source program code matching said application program; compiling the source program code to obtain a target program code; acquiring a target operating environment mirror matching the target program code from an environment mirror library, wherein at least one operating environment mirror is stored in the environment mirror library, and different operating environment mirrors correspond to different operating environments; and deploying the target program code and the target operating environment mirror onto a target cloud platform.

Abstract: The present disclosure relates to a method for configuring a priority level, a cloud platform, a system, a computing device, and a medium. The method for configuring a priority level for data on a cloud platform comprises determining the data type of received data; determining, according to the data type, a priority level specification used for describing a priority level of the received data; and calculating the priority level of the received data on the basis of the priority level specification of the received data.

Abstract: The present disclosure provides a language model based writing aid method, apparatus and system. The method includes: a server acquiring original text, where the original text may be writing text already generated and/or user input text; the server inputting the original text into a language model to generate a preset number of pieces of writing text, where the writing text and the original text have a correlation; the server sending the preset number of pieces of writing text to a frontend interface. The method of the present disclosure enables a computer to aide a user in text creating so that intelligence for writing aid is improved.