Abstract: Disclosed is a brain-on-a-chip intelligence complex control system comprising a basic module and an information interaction and training module. The latter integrates a neural signal decoding unit, reward and punishment control unit, task control model, and mapping relationship model. The neural signal decoding unit transforms neural response data into external device-recognizable control instructions. Employed for controlling the external device, the task control model creates a future target control instruction based on task feedback, retrieving the corresponding neural response. The mapping relationship model establishes connections between the brain-on-a-chip's stimulation sequence and neural responses. Calculating task completion, the reward and punishment control unit generates a reward or punishment signal based on task feedback, applying it to the brain-on-a-chip basic module. This innovative brain-on-a-chip intelligence complex enhances control and training capabilities through integrated modules.

Abstract: A method for preparing the ammonium manganese iron phosphate precursor includes mixing and grinding metal source powder and phosphorus source powder to enable a low-heating-temperature solid-state reaction of each component, and then washing and drying the obtained product to obtain the ammonium manganese iron phosphate precursor, where the metal source includes an iron source, a manganese source and an optional source of a doping element M which represents doping elements at manganese and iron sites, and the phosphorus source includes triammonium phosphate.

Abstract: The disclosure belongs to the technical fields of coast, ocean engineering and bridge engineering, and provides a method and a device for calculating a mudding boundary elevation of a headland beach adjacent to a muddy seabed. The method includes: obtaining tidal level data, wave data, beach width data and beach height data of the headland beach adjacent to the muddy seabed; according to the above data, calculating a mean high water spring, a mean low water spring, a wave height and a beach slope respectively; and according to the mean high water spring, the mean low water spring, the wave height and the beach slope, calculating the mudding boundary elevation of the beach.

Abstract: A composite positive electrode active material, a method for preparing the same, and an electric device are described. The method includes: providing positive electrode active material particles; providing a solid aluminum salt to make the solid aluminum salt cover a surface of the positive electrode active material particles; and providing a solid base to the positive electrode active material particles covered by the solid aluminum salt to make the solid aluminum salt and the solid base undergo an in situ solid-phase chemical reaction and generate a cladding layer covering the surface of the positive electrode active material particles, to obtain the composite positive electrode active material, wherein the cladding layer has alumina nanoparticles. The prepared alumina can uniformly cover the surface of the positive electrode active material particles, protect the positive electrode active material, and ensure the electrochemical performance of the positive electrode active material.

Abstract: The present invention provides a helicase BCH2X, comprising an amino acid sequence represented by any one of SEQ ID NOs: 1-3. The present invention also provides a complex structure comprising the helicase BCH2X and a binding moiety for binding polynucleotides. The present invention also provides a use of the helicase BCH2X or the complex structure comprising same in the control and characterization of polynucleotides and single-molecule nanopore sequencing.

Abstract: A gamma voltage regulation circuit set in a driver chip of a display panel, includes: an input circuit configured to determine a measured value of a power supply voltage of a power supply; a computing circuit configured to compute a variation value between the measured value and a reference value of the power supply voltage, an adjustment circuit configured to adjust a dynamic value of a reference voltage of a grayscale voltage generated by gamma correction through the variation value; and a third output circuit configured to output the grayscale voltage based on the dynamic value.

Abstract: The invention pertains to an early detection method for network unreliable information using ensemble learning, within the field of early detection technology for unreliable network data. It involves the following steps: (1) converting input text sequences into word vector sequences; (2) inputting these word vectors into three base models—Transformer, Bi-SATT-CAPS, and BiTCN—for classifying unreliable information; (3) training and predicting with these models to generate new training and test data sets; (4) weighting and merging these new data sets to create a new training set for the meta-learner SVM; (5) training the new set with the meta-learner SVM to obtain the final classification result. This method retains the text's grammatical and structural features, using only blog posts and early comments to accurately detect unreliable information. By employing an improved weight fusion strategy, the method leverages the strengths of the three base models to enhance early detection effectiveness.

Abstract: Disclosed are an accelerated test data analysis method and apparatus based on a grey forecast model, a device.

Abstract: The present disclosure discloses a method and apparatus for estimating product lifetime based on a multi-stress accelerated test, and a device. This method can be applied in the field of data processing technologies, specifically including: determining, in response to a lifetime estimation request for a target product, a target characteristic lifetime of the target product based on a target stress condition for the target product and correspondence relationships between candidate stress conditions and candidate characteristic lifetimes; and determining, based on an optimal lifetime model for the type to which the target product belongs and the target characteristic lifetime, a target average life of the target product.

Abstract: A performance degradation-based product reliability weak link evaluation method includes: acquiring a performance degradation parameter of each component of a to-be-evaluated product corresponding to each test time point; evaluating the performance degradation parameter of each component corresponding to each test time point through a fault time evaluation model, to obtain a pre-fault operating duration of each component; evaluating the pre-fault operating duration of each component through a confidence-based unreliability evaluation method, to obtain an unreliability evaluation result of each component; generating at least one component service life distribution model corresponding to each component according to the unreliability evaluation result, and selecting a corresponding target component service life distribution model; and evaluating mean time between failures corresponding to each component according to the target component service life distribution model, and selecting a reliability weak link of th

Abstract: A method for preparing a general-purpose cement is provided. Raw materials containing all of SiO2, Al2O3, CaO, MgO and Na2O (or K2O) are mixed to obtain a raw meal, which is dried and ground into a raw meal powder. The raw meal powder is oxidatively calcined at no less than 1210° C. to reach a stable phase state, and rapidly cooled to obtain a clinker predominated by glass phase. The clinker is mixed with NaOH, KOH or a combination thereof and ground to obtain the general-purpose cement. Alternatively, the clinker is ground to obtain a clinker powder, which is mixed with an aqueous NaOH solution, an aqueous KOH solution or a combination thereof for use. The NaOH and/or KOH is/are added such that a weight ratio of NaOH+0.713KOH to the clinker powder is 0-0.03:1.

Abstract: The present disclosure relates to a method and an apparatus for processing accelerated test data based on multiple performance degradation, and a device.

Abstract: The present disclosure relates to a method and an apparatus for reliability evaluation based on multiple performance degradation, a computer device, a storage medium, and a computer program product. The method includes: for each of the multiple performances of a target product, obtaining a plurality of candidate functions that the performance possibly follows, determining a target function that satisfies a preset selection condition from the plurality of candidate functions, and determining a reliability function corresponding to the performance based on the target function; determining coupling relation information between the multiple performances of the target product, and obtaining redundancy information of the multiple performances of the target product; and performing a reliability evaluation on the target product based on the coupling relation information, the redundancy information, and the reliability function of each performance.

Abstract: The present disclosure relates to a method and an apparatus for processing accelerated test data based on multiple performance degradation, and a device.

Abstract: A method of preparing alkali-activated cement by stepwise calcination with sodium chloride includes the following steps. (1) Sodium chloride, a silicate and a carbonate are mixed and finely ground to obtain a raw material powder. (2) The raw material powder is calcined sequentially at 850-1050° C. and 1240° C. or more, and cooled to obtain a clinker. (3) The clinker is mixed with at least one of sodium hydroxide and potassium hydroxide, and ground finely to produce a cement powder.

Abstract: A method for processing accelerated degradation test data based on Wiener process includes obtaining accelerated degradation test data of a to-be-tested product, selecting a target time conversion model from a predefined set of time conversion models based on the accelerated degradation test data, constructing a nonlinear Wiener degradation process based on the target time conversion model, determining a product reliability function of the to-be-tested product, and testing the reliabilities of the to-be-tested product based on the product reliability function to obtain product reliability test results of the to-be-tested products.

Abstract: Disclosed are a fault prediction method and apparatus for a power conversion device, and a power conversion system. The method includes: acquiring multiple output voltages of a detecting coil in a preset time period, wherein an electromagnetic induction is generated between the detecting coil and a switching-on circuit of a switching transistor in the power conversion device; extracting each output frequency corresponding to each output voltage of the detecting coil; predicting time when the power conversion device fails according to a change trend of each output frequency. The apparatus includes a detecting coil and a data processing device; the detecting coil is connected to the data processing device and is a closed coil; the data processing device is configured to: acquire an output voltage of the detecting coil, extract corresponding output frequency, and predict time when the power conversion device fails according to a change trend of each output frequency.

Abstract: An industrial robot motion accuracy compensation method includes: establishing a motion parameter database, wherein the motion parameter database includes a plurality of different reference operating conditions and a motion parameter of the industrial robot corresponding to each reference operating condition, and each reference operating condition is formed by combining each element in each set in a total set of operation conditions; acquiring a current operating condition of the industrial robot; determining whether there is a reference operating condition matched with the current operating condition in the motion parameter database; if yes, taking a motion parameter corresponding to the matched reference operating condition as a motion parameter corresponding to the current operating condition; if no, performing an interpolation on a motion parameter corresponding to the current operating condition, and taking an interpolation result as the motion parameter corresponding to the current operating condition.

Abstract: An industrial robot motion accuracy compensation method includes: establishing a motion parameter database, wherein the motion parameter database includes a plurality of different reference operating conditions and a motion parameter of the industrial robot corresponding to each reference operating condition, and each reference operating condition is formed by combining each element in each set in a total set of operation conditions; acquiring a current operating condition of the industrial robot; determining whether there is a reference operating condition matched with the current operating condition in the motion parameter database; if yes, taking a motion parameter corresponding to the matched reference operating condition as a motion parameter corresponding to the current operating condition; if no, performing an interpolation on a motion parameter corresponding to the current operating condition, and taking an interpolation result as the motion parameter corresponding to the current operating condition.

Abstract: A predictive maintenance system and method for intelligent manufacturing equipment is provided. The predictive maintenance system includes a first-stage predictive maintenance module, a second-stage predictive maintenance module, and a maintenance decision module. The first-stage predictive maintenance module includes an acquisition module, a human-computer interaction module, a calculation module, and a storage module. The second-stage predictive maintenance module includes a communication module, a setting module, and a prediction module. The maintenance decision module is configured to receive a first-stage remaining service life calculated by the first-stage predictive maintenance module and a second-stage remaining service life predicted by the second-stage predictive maintenance module, and determine a predictive maintenance strategy of the intelligent manufacturing equipment according to the first-stage remaining service life and the second-stage remaining service life.