Abstract: A data combination device and a data combination method are provided. The data combination device includes a storage device and a processor. The storage device is configured to store component instances. The processor is coupled to the storage device and is configured to receive a combining instruction. The processor parses a component description and data type in the combining instruction. The processor obtains a plurality of matching instances corresponding to the component description from the plurality of component instances. The processor packages the plurality of matching instances into package data.

Abstract: A processing method and a processing system of a project process are provided. The processing method includes the following steps. A processor defines a matching model according to a relationship among a plurality of pieces of document data and a relationship between the document data and a plurality of components. The processor calculates the components according to the matching model to output a plurality of recommended components in a design phase of a target project. The processor performs a packaging operation to form a plan according to a plurality of selected components. Each of a plurality of nodes in the plan includes corresponding plan coordinates. The processor specifies a first node among the nodes as a starting node to start executing the target project according to plan coordinates of an input data instance in a running phase. The first node and the input data instance have the same plan coordinates, so the project process is accordingly designed based on data.

Abstract: A data-driven execution system and an execution method thereof are provided. The data-driven execution system includes a storage device and a processor. The storage device is used for storing multiple modules. The processor is coupled to the storage device and used to execute multiple modules. The processor receives a data processing request. The processor searches a data graph according to the data processing request to obtain at least one task path. The processor generates a recommended plan according to one of the at least one task path.

Abstract: A data combination device and a data combination method are provided. The data combination device includes a storage device and a processor. The storage device is configured to store component instances. The processor is coupled to the storage device and is configured to receive a combining instruction. The processor parses a component description and data type in the combining instruction. The processor obtains a plurality of matching instances corresponding to the component description from the plurality of component instances. The processor packages the plurality of matching instances into package data.

Abstract: The disclosure provides a data compilation and execution device and a data compilation and execution method. The data compilation and execution device includes a storage device and a processor. The storage device is configured to store a compilation module and an interpretation module. The processor is coupled to the storage device and configured to receive encapsulation data. The processor executes the compilation module to match a matching compiler corresponding to the encapsulation data from compilers according to the encapsulation data. The compilation module executes a data compilation flow by the matching compiler to generate executable data according to the encapsulation data. The processor executes the interpretation module to execute a corresponding flow according to the executable data. The data compilation and execution device and the data compilation and execution method of the disclosure can automatically perform data encapsulation and task execution.

Abstract: The disclosure provides a data matching device and a data matching method. The data matching device includes a storage device and a processor. The storage device is configured to store a matching module and a data package module. The processor is coupled to the storage device and configured to receive raw data. The processor executes the data package module to generate structured and packaged data according to the raw data. The processor executes the matching module to match the structured and packaged data to a corresponding task logic. The data matching device and the data matching method in the disclosure may automatically perform data package and task matching.

Abstract: A data-driven execution system and an execution method thereof are provided. The data-driven execution system includes a storage device and a processor. The storage device is used for storing multiple modules. The processor is coupled to the storage device and used to execute multiple modules. The processor receives a data processing request. The processor searches a data graph according to the data processing request to obtain at least one task path. The processor generates a recommended plan according to one of the at least one task path.

Abstract: A dry electrode and a physiological multi-parameter monitoring equipment are disclosed. The waterproof dry electrode comprises an encapsulation, extraction electrode and a contact surface layer, wherein the extraction electrode and the contact surface layer are connected with each other and disposed in the encapsulation; the contact surface layer comprises an exposed part and an embedded part encapsulation; the encapsulation comprises flexible silica gel and hard plastic portion, the embedded part being embedded into the hard plastic portion, and the hard plastic portion being packaged in the flexible silica gel. Through the above arrangement in the present invention, the dry electrode can reach a waterproof grade of IPX7, which is higher than living waterproof grade of an ordinary dry electrode.

Abstract: Various embodiments of the teachings herein include a nonlinear model modeling method. The method may include: determining complete design point data for each of multiple target nonlinear underlying process of multiple types of equipment; establishing a descriptive formula of the process with the ratio of a similarity parameter supported by a similarity criterion to a similarity parameter based on design point data, to obtain a universal model of the process; constructing a machine learning algorithm between the parameter of the actual working condition and the variable parameter and establishing a correlation between the machine learning algorithm and the universal model; and taking the universal models of all the target nonlinear underlying processes of each type of equipment and the correlated machine learning algorithms as a universal model of the type of equipment. The universal model comprises a variable parameter that changes as a parameter of an actual working condition changes.

Abstract: Various embodiments of the teachings herein include a method for optimizing an integrated energy system comprising nonlinear devices. The method may include: receiving an optimization task containing an optimization objective; building a system of nonlinear equations on the basis of the optimization objective and a simulation model of the integrated energy system; solving the system of nonlinear equations using a linear programming algorithm to obtain an optimization result. Establishing the simulation model comprises: determining a topological structure of the integrated energy system, the topological structure comprising the devices of the integrated energy system and the connection attributes between the devices; determining general models of the devices and a connector model corresponding to the connection attributes; connecting the general models using the connector model to form a simulation model of the integrated energy system; and training the simulation model.

Abstract: Various embodiments of the teachings herein include a method for simulating an integrated energy system including nonlinear devices. The method may include: receiving a simulation task; building a system of nonlinear equations on the basis of the simulation task and a simulation model of the integrated energy system; and solving a system of nonlinear equations using a linear programming algorithm to obtain a simulation result. The process of establishing the simulation model may include: determining the topological structure of an integrated energy system, the topological structure comprising the devices of the integrated energy system and the connection attributes between the devices; determining general models of the devices and a connector model corresponding to the connection attributes; connecting the general models by means of the connector model to form a simulation model of the integrated energy system; and training the simulation model.

Abstract: Various embodiments of the teachings herein include a linearization processing method for nonlinear models. The method may include: for a nonlinear model of each piece of equipment, determining a value range of each input parameter of the model; dividing the value range of each input parameter into a plurality of subintervals based on a plurality of interpolation points; determining a plurality of input sample values in each subinterval in a balanced manner; traversing input sample value combinations of each input parameter of the model, and using the nonlinear model to obtain an output sample value combination corresponding to each input sample value combination; and using all the input sample value combinations and the corresponding output sample value combinations to generate a tensor table.

Abstract: Various embodiments of the teachings herein include a method for controlling an integrated energy system. The method may include: determining the topological structure of an integrated energy system, the topological structure representing devices of the integrated energy system and connection attributes between the devices; determining general models of the devices and a connector model corresponding to the connection attributes; connecting the general models by means of the connector model so as to form a simulation model of the integrated energy system; training the simulation model; and generating a control command of the integrated energy system on the basis of the trained simulation model.

Abstract: The present disclosure relates to a method of inducing a neuroprotective state comprising administering a Bromodomain and Extra-Terminal motif (BET) inhibitor under conditions effective to induce a neuroprotective state. Also disclosed are methods of preventing and/or treating neurodegenerative disease, methods of reducing microglial inflammation, and methods of restoring microglial homeostasis, where the methods include administering a Bromodomain and Extra-Terminal motif (BET) inhibitor.

Abstract: A dry electrode and a physiological multi-parameter monitoring equipment are disclosed. The waterproof dry electrode comprises an encapsulation, extraction electrode and a contact surface layer, wherein the extraction electrode and the contact surface layer are connected with each other and disposed in the encapsulation; the contact surface layer comprises an exposed part and an embedded part encapsulation; the encapsulation comprises flexible silica gel and hard plastic portion, the embedded part being embedded into the hard plastic portion, and the hard plastic portion being packaged in the flexible silica gel. Through the above arrangement in the present invention, the dry electrode can reach a waterproof grade of IPX7, which is higher than living waterproof grade of an ordinary dry electrode.

Abstract: An indirect heat transfer supercritical water oxidation system includes a supercritical water oxidation reactant system and an intermediate medium circuit. A control method thereof includes controlling two-process pressure and temperature increase, controlling pressure and temperature decrease and controlling normal operation. The present invention focuses on automatic control strategy of engineering practice of the indirect heat transfer supercritical water oxidation system. The system heating process adopts the idea of circulating heating, which effectively reduces the investment of the heating equipment avoids the mismatch between the working pressure of the two processes, and ensures effectiveness of the heat transfer between supercritical pressure fluid in the inner tube and the outer tube of the preheater/heat exchanger during subsequent heating process. The effective control of a reaction temperature and overpressure protection of critical equipment ensure a process effect and system safety.