Abstract: Provided is a driving device for detecting mechanical characteristics and electrical characteristics of cells. A structure of the driving device includes a piezoelectric stack, a bridge-type flexible hinge mechanism, a parallel hinge mechanism, a lead screw guide rail, a stepping motor, a linear displacement sensor, a force sensor, a ceramic needle, a first electrode, a second electrode, a cell container, an XY axis displacement platform, a positioning hole, a first metal base, a second metal base, a first metal connecting plate, a second metal connecting plate, a first pre-tightening wedge, a second pre-tightening wedge, screws, and a pre-tightening screw. During the operation of the driving device, the piezoelectric stack is driven under an excitation effect of a driving electric field signal, such that the bridge-type flexible hinge mechanism stretches, and the ceramic needle is driven by the parallel flexible hinge mechanism to move downwards.

Abstract: The present disclosure belongs to the field of radio frequency circuit design, and in particular relates to a M×N millimeter wave and terahertz planar dipole end-fire array antenna. The M×N millimeter wave and terahertz planar dipole end-fire array antenna is composed of M paths of N× end-fire linear array antennas arranged at equal intervals, and the distance d between two adjacent N× end-fire linear array antennas is less than ?, where ? is the wavelength, and both M and N are integers greater than 1. By connecting linear type feed networks of the M paths of N× end-fire linear array antennas to M-path in-phase radio frequency signal transmitter and controlling the distance between two adjacent N× end-fire linear array antennas to be less than the effective wavelength, a higher gain and a higher half-power width can be realized, and the power consumption of the transmitter can be reduced.

Abstract: The present disclosure provides a magnetic grinding device and a magnetic grinding control method, and relates to the field of machining. According to the device, a magnet platform of a grinding piece fixing table is connected with an electromagnet; the grinding piece fixing table is used for fixing a to-be-ground workpiece; an output end of a programmable power supply is connected with a coil of the electromagnet; a permanent magnet grinding rod is located above the to-be-ground workpiece; and a magnetic grinding control system is connected with the programmable power supply and is used for acquiring grinding points, on the to-be-ground workpiece, of the permanent magnet grinding rod, and controlling an output voltage of the programmable power supply by utilizing a removal amount of a blank workpiece surface shape of the to-be-ground workpiece, the grinding points and a pulse width modulation (PWM) control method.

Abstract: A face image clustering method and system based on a localized simple multiple kernel k-means is provided. The face image clustering method based on localized simple multiple kernel k-means includes the following steps: S1, acquiring face images, and preprocessing the acquired face images to obtain an average kernel matrix for each view; S2, calculating n (?×n)-nearest neighbor matrices according to the obtained average kernel matrices; S3, calculating a localized kernel matrix for each view according to the nearest neighbor matrices; S4, constructing a localized simple multiple kernel k-means clustering objective function according to the calculated localized kernel matrix for each view; S5, solving a minimum of the constructed objective function by adopting a reduced gradient descent method to obtain an optimal clustering partition matrix; and S6, performing k-means clustering on the obtained clustering partition matrix to achieve clustering.

Abstract: The present disclosure relates to an automatic detecting device for detecting flaws on a surface of a camshaft in the field of detecting device. The automatic detecting device includes a framework, which is provided with a working platform, an elevator mechanism, a first rotating elevator mechanism and a second rotating elevator mechanism. The working platform is rotatably connected with the rotating platform. The working platform is provided with a first working position; a second working position, a third working position and a fourth working position. The rotating platform is provided with a plurality of locating members. The locating member is configured for placing a test piece. The working platform is provided with an overturning mechanism, a first visual module and a second visual module.

Abstract: A later-fusion multiple kernel clustering machine learning method and system based on proxy graph improvement is provided. The method includes: S1. acquiring a clustering task and a target data sample; S2. initializing a proxy graph improvement matrix; S3. running k-means clustering and graph improvement on each view corresponding to the acquisition of the clustering task and the target data sample, and constructing an objective function by combining kernel k-means clustering and graph improvement methods; S4. cyclically solving the objective function constructed in step S3 so as to obtain a graph matrix, which is fused with basic kernel information; and S5. performing spectral clustering on the obtained graph matrix, so as to obtain a final clustering result. By means of the method, an optimized basic division not only has information of a single kernel, but can also obtain global information by means of a proxy graph.

Abstract: A high-order correlation preserved incomplete multi-view subspace clustering method and system.

Abstract: A hyperspectral image band selection method based on latent feature fusion comprises: S11, inputting a hyperspectral image cube and segmenting the inputted hyperspectral image cube into several regions by superpixel segmentation; S12, learning low-dimensional latent features corresponding to the several regions from the several regions respectively to obtain a latent feature matrix of all the regions; S13, calculating an average Laplacian matrix and an average latent feature matrix of the hyperspectral image cube; S14, fusing the latent feature matrix, the average Laplacian matrix, and the average latent feature matrix of all the regions to obtain a low-dimensional self-representation matrix of the hyperspectral image cube; and S15, clustering the low-dimensional self-representation matrix by a k-means algorithm to obtain an optimal band subset of the hyperspectral image cube.

Abstract: The present disclosure is related to the field of polymer processing, and, in particular, to a vinyl-modified nanofiller interfacial compatibilizer and a method for producing a compatibilized polymer blend. Vinyl-modified nanofillers can be used together with an initiator as a compatibilizer for polymer blends. The initiator can initiate a free radical reaction between the chains of the polymers in the blend and the vinyl groups on the surface of the vinyl-modified nanofiller, leading to in situ formation of a co-crosslinked polymer and thus compatibilization of the blend as well as improved tensile strength and modulus thereof. Results of examples showed that vinylsilane grafted onto the surface of the vinyl-modified nanofiller makes it possible for the nanofiller to be used as an effective compatibilizer. The vinyl-modified nanofillers can be used as a compatibilizer for various polymer blends systems.

Abstract: A solid-state passive evaporative cooling system includes a hydrogel body, a water supply channel, a hydrogel root, and a water supply device. One end of the water supply channel is embedded into the hydrogel body, and a plurality of water outlets are formed in an outer wall of the water supply channel embedded into the hydrogel body. A water inlet at the other end of the water supply channel is connected to the water supply device which is configured to pump an aqueous solution into the water supply channel. The hydrogel root is disposed within the water supply channel. The aqueous solution is solidified by the hydrogel body to achieve the water-saving effect. During evaporative cooling, an osmotic pressure may be spontaneously created or enhanced within the system. The water supply channel is capable of adjusting the water content of the hydrogel body and providing a water supply driving force.

Abstract: Provided is a method of increasing the effective tiller number of a rice plant, including overexpressing a gene having a nucleic acid sequence as shown in SEQ ID NO: 1 in the rice plant. The gene encodes a protein which interacts with MOC1 in the rice plant.

Abstract: A rice white leaf and panicle gene wlp3 is provided. The cDNA sequence of the white leaf and panicle gene wlp3 is shown in SEQ ID NO: 1, and the encoded amino acid sequence of the protein is shown in SEQ ID NO: 2. The rice white leaf and panicle gene wlp3 is applied to rice stress resistance and yield increase. The white leaf and panicle gene wlp3 is configured to improve cold tolerance of plants, enhance photosynthetic rate, increase plant height, leaf albinism at seedling stage, panicle albinism at heading stage, and increase panicle length at low temperature. The present disclosure obtains the rice white leaf and panicle gene wlp3 through screening and mutagenesis, which is related to the stress resistance and chlorophyll synthesis of rice. Therefore, the present disclosure provides a foundation for rice breeding.

Abstract: Molecular markers linked to main QTL for regulating resistance of rice to whitebacked planthopper are provided. The QTL is located on rice chromosome 1, with a genetic distance of 30.88-34.32 cM and a physical distance of 7203302-8007653 bp. Then the molecular markers are set on both sides of the QTL, and the molecular markers are used to screen rice varieties resistant to whitebacked planthopper, which improves the selection efficiency of ideal plant types of rice.

Abstract: A fluorescent material containing a thiophene sulfone-olefin structural unit and a preparation method thereof are provided. In the preparation method, the thiophene sulfone compounds, olefins, oxidants and additives are dissolved in the tetrahydrofuran solvent, and are subjected to a reaction under the catalytic action of the palladium catalyst, and the alkenylated thiophene sulfone products with obvious fluorescence emission characteristics of liquid and solid can be obtained. The preparation method expands the range of substrates well, featuring good regional selectivity, high yield, mild reaction conditions and simple operation.

Abstract: A spectral clustering method and system based on unified anchor and subspace learning is provided. The spectral clustering method based on unified anchor and subspace learning includes: S1: acquiring a clustering task and a target data sample; S2: performing unified anchor learning on multi-view data corresponding to the acquired clustering task and the acquired target data sample, and adaptively constructing an objective function corresponding to an anchor graph according to a learned unified anchor; S3: optimizing the constructed objective function by using an alternating optimization method to obtain an optimized unified anchor graph; and S4: performing spectral clustering on the obtained optimized unified anchor graph to obtain a final clustering result.

Abstract: A consensus graph learning-based multi-view clustering method includes: S11, inputting an original data matrix to obtain a spectral embedding matrix; S12, calculating a similarity graph matrix and a Laplacian matrix based on the spectral embedding matrix; S13, applying spectral clustering to the calculated similarity graph matrix to obtain spectral embedding representations; S14, stacking inner products of the normalized spectral embedding representations into a third-order tensor and using low-rank tensor representation learning to obtain a consistent distance matrix; S15, integrating spectral embedding representation learning and low-rank tensor representation learning into a unified learning framework to obtain a objective function; S16, solving the obtained objective function through an alternative iterative optimization strategy; S17, constructing a consistent similarity graph based on the solved result; and S18, applying spectral clustering to the consistent similarity graph to obtain a clustering resul

Abstract: An unsupervised feature selection method based on latent space learning and manifold constraints includes: S11, inputting an original data matrix to obtain a feature selection model; S12, embedding latent space learning into the feature selection model to obtain a feature selection model with the latent space learning; S13, adding a graph Laplacian regularization term into the feature selection model with the latent space learning to obtain an objective function; S14, solving the objective function by adopting an alternative iterative optimization strategy; and S15, sequencing each feature in the original matrix, and selecting the first k features to obtain an optimal feature subset. Feature selection is performed in a learned potential latent space, and the space is robust to noise. The potential latent space is modeled by non-negative matrix decomposition of a similarity matrix, and the matrix decomposition can unambiguously reflect relationships between data instances.

Abstract: A multi-view clustering method and system based on matrix decomposition and multi-partition alignment are provided.

Abstract: A citation network graph representation learning system and method based on multi-view contrastive learning is provided. The citation network graph representation learning system involved in the present application comprises: a sample construction module, which is configured to construct a corresponding negative sample based on an original graph; a graph enhancement module, which is configured to obtain a positive sample graph and a negative sample graph; a fusion module, which is configured to obtain a consensus representation of the positive sample graph and the negative sample graph by means of a cross view concentration fusion layer; a mutual information estimation module, which is configured to compare learning representations of positive sample pairs and negative sample pairs by means of a discriminator; and a hard sample mining module, which is configured to represent the consistency between the negative sample pairs according to a pre-calculated affinity vector, and select and reserve nodes.

Abstract: A system for unsupervised deep representation learning based on image translation is provided. The system includes an image translation transformation module used for performing a random translation transformation on an image and generating an auxiliary label; an image mask module connected with the image translation transformation module and used for applying a mask to the image after translation transformation; a deep neural network connected with the image mask module and used for predicting an actual auxiliary label of the image after the mask is applied and learning the deep representation of the image; a regression loss function module connected with the deep neural network and used for updating parameters of the deep neural network based on a loss function; and a feature extraction module connected with the deep neural network and used for extracting the representation of the image.