The present disclosure relates to a method and device for removing background noise in microscopic imaging based on frequency-domain modulation. The method includes irradiating a surface of a sample to be measured by simultaneously irradiating the surface of the sample by utilizing two beams from two laser devices. One of the two beams passes through a 0˜2π vortex phase plate and then focuses on the sample to be measured to form a high-energy hollow spot, and the other of the two beams focuses on the sample to be measured to form a low-energy solid spot. The method further includes modulating the two beams in time-domain simultaneously using an electro-optic modulator and demodulating signal light at different frequencies using a lock-in amplifier, then removing the background noise by a differential process to realize a high signal-to-noise ratio super-resolution image.
A method for detecting a surface defect of a thermal cup, a system thereof, a device and a medium are provided. The method includes: acquiring thermal cup images from different angles, and preprocessing thermal cup images to generate enhanced thermal cup images; performing convolution operation for a first-order derivative of a Gaussian function on the enhanced thermal cup images to determine first filtered images; and determining defect regions according to the first filtered images and the thermal cup images by using a threshold segmentation method based on a bilinear interpolation and a second-order derivative of the Gaussian function. The set parameters are adjusted based on a gradient change and the current illumination environment. The defect regions include a final pit defect region, an upper side polishing print defect region and a lower side polishing print defect region.
A lateral and vertical DEP method for micro-nano biological and metabolite sensors and actuators using two electric field intensities. The method specifically comprises the following steps: S1, before a metal etching process, performing resist plasma etching to form a resist profile at a side wall, wherein a high-pressure baseline formulation comprises oxygen, nitrogen, and argon in a ratio of 1:4:140 at a pressure of 1600 mT and a radiofrequency power of 1300 watts, used to generate a resist with a pre-designed angle; S2, performing metal etching, wherein a baseline instruction comprises chlorine, boron trichloride, and argon in a ratio of, but not limited to, 1:0.4:0.2, at a pressure of 8 mT, with a source power preferably of 1200 watts and a bias power preferably of 175 watts; and S3, performing metal profiling to measure the remaining thickness. The method enables a lateral attractive force of PDEP at Y in a medium.
B01D 57/02 - Séparation, autre que la séparation de solides, non entièrement couverte par un seul groupe ou sous-classe, p. ex. par électrophorèse
4.
LATERAL AND VERTICAL DIELECTROPHORESIS METHOD FOR MICRO/NANO-SCALE BIOLOGICAL AND METABOLIC SENSORS AND ACTUATORS USING TWO HIGH-INTENSITY ELECTRIC FIELDS
Disclosed is a lateral and vertical dielectrophoresis method for micro/nano-scale biological and metabolic sensors and actuators using two high-intensity electric fields, including: S1. performing resist plasma etching before metal etching to form a resist profile at a sidewall, where a high-pressure baseline formulation includes oxygen, nitrogen and argon in a ratio of 1:4:140, with a pressure of 1600 mT, and an RF power of 1300 W, which is used to produce a pre-designed angle resist; S2. performing metal etching, a baseline instruction includes chlorine, boron trichloride, and argon, with a preferred ratio of 1:0.4:0.2, a pressure of 8 mT, a source power of preferably 1200 W, and a bias power of preferably 175 W; and S3. performing metal profiling measurement to measure a remaining thickness. The method enables manipulation, separation, and fractionation of target and non-target particles in the medium through lateral positive dielectrophoresis attractive force at Y.
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.
G01N 3/08 - Recherche des propriétés mécaniques des matériaux solides par application d'une contrainte mécanique par application d'efforts permanents de traction ou de compression
G01N 27/22 - Recherche ou analyse des matériaux par l'emploi de moyens électriques, électrochimiques ou magnétiques en recherchant l'impédance en recherchant la capacité
A plasma generator and an air purifier. Discharge electrodes (103, 104) are used for single/dual-electrode discharge, and the discharge electrodes (103, 104) each comprise a base electrode and a nano array growing on the base electrode in situ. Positive and negative ions can be independently/simultaneously released, and ozone with lower concentration can be generated.
A61L 2/14 - Procédés ou appareils de désinfection ou de stérilisation de matériaux ou d'objets autres que les denrées alimentaires ou les lentilles de contactAccessoires à cet effet utilisant des phénomènes physiques du plasma, c.-à-d. des gaz ionisés
F24F 8/30 - Traitement, p. ex. purification, de l'air fourni aux locaux de résidence ou de travail des êtres humains autrement que par chauffage, refroidissement, humidification ou séchage par ionisation
7.
SHORT-WAVE ULTRAVIOLET AND PLASMA-COUPLED COLD CHAIN TRANSPORTATION INTEGRATED DEVICE
Disclosed in the present application is a short-wave ultraviolet and plasma-coupled cold chain transportation integrated device, comprising a transportation part, a sterilization part, a sorting part, a packaging part and a refrigeration part, wherein the sterilization part, the sorting part, the packaging part and the refrigeration part are all arranged in the transportation part. Integrated sterilization and preservation operations for fruits and vegetables are implemented during the whole process integrating feeding, sorting, packaging, precooling, transportation, warehousing and the like, so that the whole process is sterile, thus effectively prolonging the preservation time of fruits and vegetables.
A23B 7/015 - Conservation par irradiation ou traitement électrique sans effet de chauffage
A61L 2/10 - Procédés ou appareils de désinfection ou de stérilisation de matériaux ou d'objets autres que les denrées alimentaires ou les lentilles de contactAccessoires à cet effet utilisant des phénomènes physiques des radiations des ultraviolets
A61L 2/14 - Procédés ou appareils de désinfection ou de stérilisation de matériaux ou d'objets autres que les denrées alimentaires ou les lentilles de contactAccessoires à cet effet utilisant des phénomènes physiques du plasma, c.-à-d. des gaz ionisés
A61L 9/20 - Désinfection, stérilisation ou désodorisation de l'air utilisant des phénomènes physiques des radiations des ultraviolets
B07B 13/04 - Classement ou triage des matériaux solides par voie sèche non prévu ailleursTriage autrement que par des dispositifs commandés indirectement selon la taille
A23N 15/00 - Machines ou appareils destinés à d'autres traitements des fruits ou des légumes pour les besoins de l'hommeMachines ou appareils pour écimer ou peler les bulbes à fleurs
B60P 3/20 - Véhicules adaptés pour transporter, porter ou comporter des charges ou des objets spéciaux pour le transport de marchandises réfrigérées
8.
USE OF GENE IN INCREASING BIOMASS AND SEED YIELD OF PLANT
A use of a gene negatively regulating the biomass and seed yield of a plant. The gene is a AT3G28990 gene having a nucleotide sequence as shown in SEQ ID NO: 1, and the biomass and seed yield of a plant can be increased by knocking out the AT3G28990 gene in the plant.
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
C07K 14/415 - Peptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant de végétaux
C12N 15/29 - Gènes codant pour des protéines végétales, p. ex. thaumatine
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
9.
FACE IMAGE CLUSTERING METHOD AND SYSTEM BASED ON LOCALIZED SIMPLE MULTIPLE KERNEL K-MEANS
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 (Σ×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.
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p. ex. de visages similaires sur les réseaux sociaux
10.
LATER-FUSION MULTIPLE KERNEL CLUSTERING MACHINE LEARNING METHOD AND SYSTEM BASED ON PROXY GRAPH IMPROVEMENT
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.
G06F 18/23213 - Techniques non hiérarchiques en utilisant les statistiques ou l'optimisation des fonctions, p. ex. modélisation des fonctions de densité de probabilité avec un nombre fixe de partitions, p. ex. K-moyennes
A high-order correlation preserved incomplete multi-view subspace clustering method and system. The method comprises: S11, inputting an original data matrix, and converting original data into an observed part and an incomplete part; S12, obtaining a plurality of affinity matrices according to self-representation characteristics of the original data; S13, mining a high-order correlation between the plurality of affinity matrices by tensor factorization; S14, learning a unified affinity matrix from the plurality of affinity matrices, so as to obtain a global affinity matrix; S15, constructing a hypergraph on the basis of the global affinity matrix, and constraining an incomplete part of incomplete multi-view data by using a hypergraph-induced Laplacian matrix; S16, integrating the global affinity matrix, the tensor factorization and the hypergraph-induced Laplacian matrix constraint into a unified learning framework; S17, solving the obtained objective function by an alternating iterative optimization strategy; and S18, applying spectral clustering to the global affinity matrix.
G06F 18/2321 - Techniques non hiérarchiques en utilisant les statistiques ou l'optimisation des fonctions, p. ex. modélisation des fonctions de densité de probabilité
The present invention belongs to the field of crop genetic breeding, and particularly relates to a method for improving the rice yield per plant by means of using a tillering promoting gene. Disclosed in the present invention is the use of Os03g0280400 gene in improving rice tillering promotion, the nucleotide sequence of the Os03g0280400 gene being as shown in SEQ ID NO: 1. Further provided in the present invention is a method for improving the rice yield per plant by means of using the new rice tillering promoting functional gene Os03g0280400.
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
A01H 6/46 - Gramineae ou Poaceae, p. ex. ivraie, riz, blé ou maïs
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
C12N 15/29 - Gènes codant pour des protéines végétales, p. ex. thaumatine
13.
HYPERSPECTRAL IMAGE BAND SELECTION METHOD AND SYSTEM BASED ON LATENT FEATURE FUSION
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.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/58 - Extraction de caractéristiques d’images ou de vidéos relative aux données hyperspectrales
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
14.
THREE-DIMENSIONAL HOLLOW HEAT EXCHANGER AND USE THEREOF
A three-dimensional hollow heat exchanger and a use thereof. The three-dimensional hollow heat exchanger is formed after a plurality of microstructural channel sheets are stacked and atoms are diffused and bonded. The three-dimensional hollow heat exchanger comprises working fluid channel groups located between adjacent microstructural channel sheets. The microstructural channel sheets each comprise a heat exchange area, and atom diffusion and bonding areas located on two sides of the heat exchange area in an O-X direction, wherein a plurality of microstructures are arranged in the heat exchange area, and the microstructures are each provided with a plurality of holes used for adsorbing tiny impurity particles in a liquid. In the present invention, tiny impurity particles in a working fluid are dispersed by means of a large number of working fluid channel groups, and a plurality of holes are provided in microstructures, such that the tiny impurity particles in the working fluid are induced to enter and be adsorbed in the holes, so as to reduce the tiny impurity particles in the working fluid, thereby reducing the risk of freezing caused by the tiny impurity particles in the working fluid serving as ice nuclei.
F28D 9/00 - Appareils échangeurs de chaleur comportant des ensembles de canalisations fixes en forme de plaques ou de laminés pour les deux sources de potentiel calorifique, ces sources étant en contact chacune avec un côté de la paroi d'une canalisation
F28F 3/02 - Éléments ou leurs ensembles avec moyens pour augmenter la surface de transfert de chaleur, p. ex. avec des ailettes, avec des évidements, avec des ondulations
15.
RICE WHITE LEAF AND PANICLE GENE WLP3 AND APPLICATION THEREOF IN RICE STRESS RESISTANCE AND YIELD INCREASE
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.
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.
C12Q 1/6895 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour la détection ou l’identification d’organismes pour les plantes, les champignons ou les algues
17.
RICE WHITE LEAF AND PANICLE GENE WLP3 AND APPLICATION THEREOF IN RICE STRESS RESISTANCE AND YIELD INCREASE
Provided are a rice white leaf and panicle gene wlp3, a cDNA sequence thereof being as shown in SEQ ID NO. 1, and a coding amino acid sequence being as shown in SEQ ID NO. 2. The rice white leaf and panicle gene wlp3 is applied to improving rice stress resistance and increasing rice yield, wherein the white leaf and panicle gene wlp3 improves the plant cold resistance, enhances the photosynthetic rate, increases the plant height, whitens the leaves in the seedling stage, whitens the panicles in the heading stage and increases the panicle length at low temperatures. The rice white leaf and panicle gene wlp3 is obtained by screening mutagenesis, the gene is related to the rice stress resistance and the amount of chlorophyll synthesis, and provides a basis for rice breeding.
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/46 - Gramineae ou Poaceae, p. ex. ivraie, riz, blé ou maïs
18.
MAJOR QTL LINKAGE MOLECULAR MARKER FOR SOGATELLA FURCIFERA RESISTANCE IN RICE, AND USE
Disclosed is a major QTL linkage molecular marker for regulating sogatella furcifera resistance in rice. The QTL is located on rice chromosome 1, the genetic distance is 30.88-34.32 cM, and the physical distance is 7203302-8007653 bp; further, molecular markers are arranged on both sides of the QTL, rice varieties resistant to sogatella furcifera are screened via said molecular markers, and the screening efficiency of ideal rice types is improved.
C12Q 1/68 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des acides nucléiques
C12N 15/11 - Fragments d'ADN ou d'ARNLeurs formes modifiées
19.
FLUORESCENT MATERIAL CONTAINING THIOPHENE SULFONE-OLEFIN STRUCTURAL UNIT AND PREPARATION METHOD THEREOF
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.
C07D 333/54 - Benzo [b] thiophènesBenzo [b] thiophènes hydrogénés avec uniquement des atomes d'hydrogène, des radicaux hydrocarbonés ou des radicaux hydrocarbonés substitués, liés directement aux atomes de carbone de l'hétérocycle
C07D 333/56 - Radicaux substitués par des atomes d'oxygène
C09K 11/06 - Substances luminescentes, p. ex. électroluminescentes, chimiluminescentes contenant des substances organiques luminescentes
20.
SPECTRAL CLUSTERING METHOD AND SYSTEM BASED ON UNIFIED ANCHOR AND SUBSPACE LEARNING
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.
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 result. A consistent similarity graph for clustering is constructed based on spectral embedding features.
G06F 18/2323 - Techniques non hiérarchiques basées sur la théorie des graphes, p. ex. les arbres couvrants de poids minimal [MST] ou les coupes de graphes
G06F 17/14 - Transformations de Fourier, de Walsh ou transformations d'espace analogues
22.
UNSUPERVISED FEATURE SELECTION METHOD BASED ON LATENT SPACE LEARNING AND MANIFOLD CONSTRAINTS
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.
A multi-view clustering method and system based on matrix decomposition and multi-partition alignment are provided. The multi-view clustering method based on matrix decomposition and multi-partition alignment includes: S1: acquiring a clustering task and a target data sample; S2: decomposing multi-view data corresponding to the acquired clustering task and the acquired target data sample through a multi-layer matrix to obtain a basic partition matrix of each view; S3: fusing and aligning the obtained basic partition matrix of each view by using column transformation to obtain a consistent fused partition matrix; S4: unifying the obtained basic partition matrix of each view and the consistent fused partition matrix, and constructing an objective function corresponding to the unified partition matrix; S5: optimizing the constructed objective function to obtain an optimized unified partition matrix; and S6: performing spectral clustering on the obtained optimized unified partition matrix to obtain a final clustering result.
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.
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
25.
LATE FUSION MULTI-VIEW CLUSTERING METHOD AND SYSTEM BASED ON LOCAL MAXIMUM ALIGNMENT
A late fusion multi-view clustering method and system based on local maximum alignment are provided. The late fusion multi-view clustering method based on local maximum alignment includes the following steps: S1: acquiring a clustering task and a target data sample; S2: initializing a permutation matrix of each view and a combination coefficient of each view, and performing average partition of kernel k-means clustering on an average kernel to obtain a neighbor matrix of each view; S3: calculating basic partition of each view, and establishing a late fusion multi-view clustering objective function based on maximum alignment; S4: acquiring basic partition having local information, and establishing a late fusion multi-view clustering objective function based on local maximum alignment; S5: solving the established late fusion multi-view clustering objective function based on local maximum alignment in a cyclic manner to obtain optimal partition; and S6: performing k-means clustering on the optimal partition.
G06F 18/23213 - Techniques non hiérarchiques en utilisant les statistiques ou l'optimisation des fonctions, p. ex. modélisation des fonctions de densité de probabilité avec un nombre fixe de partitions, p. ex. K-moyennes
26.
CITATION NETWORK GRAPH REPRESENTATION LEARNING SYSTEM AND METHOD BASED ON MULTI-VIEW CONTRASTIVE LEARNING
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.
A multi-modal adaptive fusion deep clustering model based on an auto-encoder includes an encoder structure, a multi-modal adaptive fusion layer, a decoder structure and a deep embedding clustering layer. The encoder is configured to enable a dataset to be respectively subjected to three types of nonlinear mappings of the auto-encoder, a convolutional auto-encoder and a convolutional variational auto-encoder to obtain potential features, respectively. The multi-modal adaptive feature fusion layer is configured to fuse the potential features into a common subspace in an adaptive spatial feature fusion mode to obtain a fused feature. The decoder is configured to decode the fused feature by using a structure symmetrical to the encoder to obtain a decoded reconstructed dataset. The deep embedding clustering layer is configured to cluster the fused feature Z and obtain a final accuracy ACC by comparing a clustering result with a true label.
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.
Provided is the use of a gene in promoting the biosynthesis of lycopene in tomato fruits. The gene is Solyc05g004600 having a nucleotide sequence as shown in SEQ ID NO: 1, and knocking out the Solyc05g004600 gene in tomatoes can promote the biosynthesis of lycopene in plant fruits.
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/82 - Solanaceae, p. ex. poivron, tabac, pomme de terre, tomate ou aubergine
Disclosed is a magnetorheological fluid automobile bumper, and belongs to the field of automobile bumpers. The magnetorheological fluid automobile bumper comprises a rear bumper body, wherein two front bumper bodies are symmetrically hinged to the front side of the rear bumper body, the ends, close to each other, of the two front bumper bodies are in butt joint with each other, a connecting rod is jointly installed between the front bumper body and the rear bumper body, one end of the connecting rod is hinged to the front bumper body, and the other end of the connecting rod is slidably installed with the rear bumper body; and a plurality of magnetorheological fluid buffers are installed on the rear side of the rear bumper body.
B60R 19/02 - Pare-chocs, c.-à-d. éléments pour recevoir ou absorber les chocs pour protéger les véhicules ou dévier les chocs provenant d'autres véhicules ou objets
F16F 9/53 - Moyens pour le réglage des caractéristiques des amortisseurs en faisant varier la viscosité du fluide, p. ex. électromagnétiques
A high-stability large-torque magnetorheological fluid clutch, which is aimed at solving the problems of magnetorheological fluid (8) in the present magnetorheological fluid clutches being prone to settling, and the torque of the magnetorheological fluid clutches being insufficient. Firstly, in order to prevent the settlement of a magnetorheological fluid (8), a blade (15-3) is mounted on an input plate body (15-2), and when a clutch runs in a power interruption mode, the blade (15-3) stirs the magnetorheological fluid (8), such that the settled magnetorheological fluid (8) is uniformly mixed. Secondly, in order to improve the maximum transmission torque of the magnetorheological fluid clutch, an excitation magnetic field is increased using a mode in which permanent magnets (5, 11) are connected in series to electromagnets (6, 10); moreover, a third electric push rod (14) is used for pushing an input plate (15), such that the magnetorheological fluid (8) operates in a shearing-extrusion operation mode, thereby improving the yield stress of the magnetorheological fluid (8), so as to improve the maximum transmission torque of the magnetorheological fluid clutch.
F16D 37/02 - Embrayages dans lesquels le mouvement d'entraînement est transmis au travers d'un milieu composé de fines particules, p. ex. par réaction centrifuge à la vitesse les particules étant aimantables
32.
High-stability and large-torque magnetorheological fluid clutch
The present disclosure is a high-stability and large-torque magnetorheological fluid clutch. Firstly, in order to prevent sedimentation of the magnetorheological fluid, blades are installed on the disc body of an input disc. When the clutch operates in a power interruption mode, the blades can stir the magnetorheological fluid, so that the sedimented magnetorheological fluid is uniformly mixed. Secondly, in order to improve the maximum transmission torque of the magnetorheological fluid clutch, an excitation magnetic field is increased in a mode that a permanent magnet and an electromagnet are connected in series. Meanwhile, a third electric push rod is used for pushing the input disc, and the magnetorheological fluid works in a shearing-extruding working mode, so that the yield stress of the magnetorheological fluid is improved. Therefore, the maximum transmission torque of the magnetorheological fluid clutch is improved.
F16D 37/02 - Embrayages dans lesquels le mouvement d'entraînement est transmis au travers d'un milieu composé de fines particules, p. ex. par réaction centrifuge à la vitesse les particules étant aimantables
F16D 37/00 - Embrayages dans lesquels le mouvement d'entraînement est transmis au travers d'un milieu composé de fines particules, p. ex. par réaction centrifuge à la vitesse
33.
Method for synthesizing dibenzocycloheptane derivatives by series cyclization of free radicals under electrooxidation conditions
Disclosed is a method for synthesizing dibenzcycloheptanone derivatives by series cyclization of free radicals under electrooxidation conditions, belonging to the technical field of organic synthesis. The disclosed method includes: taking o-propionyl biphenyl analogues and sodium benzenesulfinate analogues as raw materials, and electrifying and reacting the raw materials in an electrolytic cell to obtain dibenzocycloheptane derivatives. According to the application, benzenesulfinate anion is oxidized into benzenesulfonyl radical under the condition of constant current and electrolyte, then the radical attacks the a-position of alkynone reactant carbonyl to obtain an alkenyl radical, then the alkenyl radical is cyclized and added to another benzene ring by 7-endo-trig to realize the construction of seven-membered ring, and finally the dibenzocycloheptane analogue is obtained by deprotonation.
C07C 49/323 - Composés saturés comportant des groupes cétone liés à des cycles polycycliques avec les groupes cétones liés à des systèmes cycliques condensés
The present invention belongs to the field of soft sensors. Disclosed is a trifurcate device for soft sensors. The trifurcate device for soft sensors comprises a trifurcate support mechanism and several soft sensors, wherein the soft sensors are mounted on the trifurcate support mechanism in a stretched state, and are uniformly stressed; the trifurcate support mechanism comprises a top circular cover-shaped connector, an intermediate sliding connector and a bottom trifurcate connector, which are coaxial with each other, the sliding connector being perpendicular to the circular cover-shaped connector and the trifurcate connector; and a hinged structure is provided inside each of the circular cover-shaped connector and the trifurcate connector; and one end of each soft sensor is fixed to the trifurcate connector, and the other end of the soft sensor is fixed to the circular cover-shaped connector. The circular cover-shaped connector drives the sliding connector to move vertically or obliquely move after the circular cover-shaped connector is subjected to a force in a vertical or horizontal direction, so that the soft sensors are driven to have stretching or retraction deformation, thereby generating a capacitance change response; the displacement and the inclination angle of a bearing can be simultaneously measured according to the change of the capacitance; and thus the structure of the trifurcate device is simple, and the application range thereof is wide.
The invention refers to the function and application of a disease-resistance gene Xa7 highly resistant to the bacterial blight of rice, belonging to the field of plant genetics. The invention discloses a gene Xa7 with high resistance to rice bacterial blight. The nucleotide sequence of gene Xa7 is shown in SEQ ID No: 1. The invention also provides the usage of the gene Xa7 to improve the resistance of rice to bacterial blight.
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 λ, where λ 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.
The present application relates to a knowledge graph recommendation method and system based on an improved KGAT model. The method comprises: constructing a domain knowledge graph; taking a user as a node of the domain knowledge graph, adding historical interaction of the user and an article as an edge of a relationship into the knowledge graph, and constructing a collaborative knowledge graph; using the improved KGAT model to learn the collaborative knowledge graph, to obtain vectorized representations of the user and the article and weight information of adjacent edges of article nodes; sorting all article sets to be recommended, and selecting the first N articles as an article set to be recommended to the user; generating a recommendation reason on the basis of the sorting result and the weight information of the adjacent edges of the article nodes corresponding to the sorting result in the collaborative knowledge graph; and when the user requests recommendation, generating a recommendation list from the recommendation reason and the article, and returning the recommendation list to the user. According to the present application, the personalized recommendation list is generated for the user, and meanwhile, personalized recommendation reasons can be generated, such that the credibility of the recommendation result is improved.
diboride-silicon carbide (SiC) multiphase ceramic, including: (S1) mixing a transition metal oxide mixed powder, nano carbon black and a silicon hexaboride (SiB6) powder to obtain a precursor powder; and (S2) subjecting the precursor powder to pressureless sintering to obtain the high-entropy carbide-high-entropy diboride-SiC multiphase ceramic with a relative density of 96% or more.
C04B 35/58 - Produits céramiques mis en forme, caractérisés par leur compositionCompositions céramiquesTraitement de poudres de composés inorganiques préalablement à la fabrication de produits céramiques à base de non oxydes à base de borures, nitrures ou siliciures
C04B 35/626 - Préparation ou traitement des poudres individuellement ou par fournées
C04B 35/65 - Frittage par réaction de compositions contenant un métal libre ou du silicium libre
39.
Automatic detecting device for detecting flaws on surface of camshaft
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.
The present disclosure provides a digital image sensing device with a light intensifier, its structure includes a locating handle, a button, a host, a light intensifier, a regulating mechanism and a sensor, wherein the locating handle is connected to the host, the host fits with the light intensifier through the button in a form of electric connection, and the regulating mechanism is arranged between the light intensifier and the sensor; a stopping device and an interweaving device are arranged on a force-assisted body, and mutual fit is performed on a fillet cylinder through the stopping device and the interweaving device; when a guide rail has a closing tendency, a drum bulge inside the guide rail will firstly push the fillet cylinder to roll upwards, the interweaving device is guided to be located on a stabilizer through a pulling sheet.
H04N 23/54 - Montage de tubes analyseurs, de capteurs d'images électroniques, de bobines de déviation ou de focalisation
H04N 23/68 - Commande des caméras ou des modules de caméras pour une prise de vue stable de la scène, p. ex. en compensant les vibrations du boîtier de l'appareil photo
41.
IMAGE SUPER-RESOLUTION ENLARGEMENT MODEL AND METHOD
SFDFGLRFFBGHRFFBRECLR0DF-LDF-HDF-LGLRFFBDF-HGHRFFBGLRFFBGHRFFBSRSR. The present invention can achieve high image reconstruction performance and good image enlargement effect.
The present application discloses a facial image clustering method and system based on localized simple multi-kernel k-means. The facial image clustering method based on localized simple multi-kernel k-means comprises the steps of: S1. acquiring a facial image, preprocessing the acquired facial image, and obtaining an average kernel matrix of various views; S2. according to the obtained average kernel matrix, calculating n number of (τ×n)-neighbor matrices; S3. according to the neighbor matrices, calculating a localized kernel matrix of various views; S4. according to the calculated localized kernel matrix of various views, constructing a localized simple multi-kernel k-means clustering objective function; S5. solving the minimum value of the constructed objective function by using a reduced gradient descent method, and obtaining an optimal clustering division matrix; and S6. performing k-means clustering on the obtained clustering division matrix to achieve clustering.
Disclosed in the present application are a multi-view text clustering method and system based on one-step late fusion. The multi-view text clustering method based on one-step late fusion, which is involved in the present application, comprises the steps of: S1, acquiring text data, and processing the acquired text data to obtain a consensus clustering matrix; S2, decomposing the obtained consensus clustering matrix to obtain a decomposed consensus clustering matrix; S3, on the basis of the decomposed consensus clustering matrix, constructing a target function of a consensus matrix and a clustering label; S4, by means of an alternating optimization method, solving the constructed target function to obtain an optimal matrix; and S5, clustering the obtained optimal matrix to realize clustering.
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.
A non-contact facial blood pressure measurement method based on 3D CNN is disclosed, which belongs to the technical field of computer vision. The method includes the following steps. S110: collecting an actual face video sample and training a blood pressure prediction model based on face images using 3D CNN neural network. S120: obtaining a face video in real time through a HD camera. S130: recognizing face key points in the face video obtained in S120 through dlib face recognition model, selecting a face region of interest, and extracting face images from the region. S140: performing a wavelet transform operation on the face images extracted in S130 to remove noise. S150: inputting seven consecutive frames of the face images into the 3D CNN blood pressure prediction model trained in S110 to obtain a blood pressure value of the measured person. The disclosure realizes non-contact facial blood pressure measurement.
G06V 40/16 - Visages humains, p. ex. parties du visage, croquis ou expressions
A61B 5/021 - Mesure de la pression dans le cœur ou dans les vaisseaux sanguins
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
47.
CITATION NETWORK GRAPH REPRESENTATION LEARNING SYSTEM AND METHOD BASED ON MULTI-VIEW CONTRASTIVE LEARNING
Disclosed in the present application are a citation network graph representation learning system and method based on multi-view contrastive learning. The citation network graph representation learning system involved in the present application comprises: a sample construction module, which is configured to take an original graph node representation as a positive sample, and construct a corresponding negative sample on the basis of an original graph; a graph enhancement module, which is configured to enhance a node feature of the positive sample on the basis of a personalized page ranking algorithm and a Laplacian smoothing algorithm, so as to obtain a positive sample graph and a negative sample graph; a fusion module, which is configured to extract a positive sample graph representation and a negative sample graph representation on the basis of an encoder, integrate the positive sample graph representation and the negative sample graph representation, and 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 difficult 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 that have more difficulty in expressing global or neighbor information.
A post-fusion multi-view clustering method and system based on local maximum alignment. The post-fusion multi-view clustering method based on local maximum alignment comprises the following steps: S1, acquiring a clustering task and a target data sample; S2, initializing a permutation matrix of each view and a combination coefficient of each view, and performing average division of kernel k-means clustering on an average kernel to obtain a neighbor matrix of each view; S3, calculating basic division of each view, and establishing a post-fusion multi-view clustering objective function based on maximum alignment; S4, acquiring basic division having local information, and establishing a post-fusion multi-view clustering objective function based on local maximum alignment by combining the neighbor matrix of each view and step S3; S5, solving the established post-fusion multi-view clustering objective function based on local maximum alignment by using a circulation means to obtain optimal division after fusing each basic division; and S6, performing k-means clustering on the optimal division to obtain a clustering result.
Disclosed are an entity alignment method and apparatus for multi-modal knowledge graphs, and a storage medium. The present invention comprises: acquiring data of a first multi-modal knowledge graph and a second multi-modal knowledge graph, and extracting therefrom entities that require alignment; processing multi-modal data of the entities to obtain each modal vector of the entities, and performing early fusion and late fusion according to each modal vector; combining the result of early fusion and the result of late fusion to obtain a multi-modal embedded vector; and performing entity alignment according to the multi-modal embedded vector. By using the method of the present invention, entity alignment for multi-modal knowledge graphs can be implemented, thus solving the problem of inconsistency between multi-modal knowledge expressions. The present invention can be widely applied to the technical field of knowledge graphs.
Disclosed in the present application are a spectral clustering method and system based on unified anchor and subspace learning. The spectral clustering method based on unified anchor and subspace learning, to which method the present application relates, comprises: 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 target data sample, and constructing, according to a learned unified anchor and in a self-adaptive manner, a target function corresponding to an anchor chart; S3, optimizing, by using an alternative optimization method, the constructed target function to obtain an optimized unified anchor chart; and S4, performing spectral clustering on the obtained optimized unified anchor chart to obtain a final clustering result.
A multi-view clustering method and system based on matrix decomposition and multi-partition alignment. The method comprises: S1, obtaining a clustering task and a target data sample; S2, decomposing multi-view data corresponding to the obtained clustering task and the obtained target data sample by means of a multi-layer matrix so as to obtain a basic partition matrix of each view; S3, fusing and aligning the obtained basic partition matrixes of all the views by using column transformation, so as to obtain a consistent fused partition matrix; S4, unifying the obtained basic partition matrix of each view and the consistent fused partition matrix, and constructing a target function corresponding to the unified partition matrix; S5, optimizing the constructed target function by using an alternating optimization method, so as to obtain an optimized unified partition matrix; and S6, performing spectral clustering on the obtained optimized unified partition matrix to obtain a final clustering result.
4) grown on the nickel foam prepared by the present invention still has a high specific capacity at a low temperature, and the assembled supercapacitor can withstand low temperature, and thus has great application prospects.
The present invention relates to the field of crop genetic breeding and relates to a gene for improving the photosynthesis efficiency of rice and a use method thereof. Disclosed in the present invention is a use of a gene for improving the photosynthesis efficiency of rice: Os07g0101400 gene is over-expressed in rice, such that the photosynthesis efficiency of rice leaves is improved, the yield is increased, the gene has potential application value in rice high-yield breeding, and the nucleotide sequence of the Os07g0101400 gene is shown as SEQ ID NO: 1.
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/46 - Gramineae ou Poaceae, p. ex. ivraie, riz, blé ou maïs
54.
LATER-FUSION MULTIPLE KERNEL CLUSTERING MACHINE LEARNING METHOD AND SYSTEM BASED ON PROXY GRAPH IMPROVEMENT
A later-fusion multiple kernel clustering machine learning method and system based on proxy graph improvement. The involved later-fusion multiple kernel clustering machine learning method based on proxy graph improvement comprises the steps of: 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, which is more beneficial to fusing views, such that a learned proxy graph can better fuse information of each kernel matrix, thereby realizing an aim of improving a clustering effect.
Disclosed in the present application are a hyperspectral image band selection method and system based on latent feature fusion. The hyperspectral image band selection method based on latent feature fusion comprises: S11, inputting a hyperspectral image cube, and segmenting the input hyperspectral image cube into several areas by using super-pixel segmentation; S12, respectively learning, from the several areas, low-dimensional latent features corresponding to the several areas, so as to obtain latent feature matrices of all areas; S13, calculating an average Laplacian matrix and an average latent feature matrix of the hyperspectral image cube; S14, fusing the latent feature matrices of all the areas, the average Laplacian matrix and the average latent feature matrix to obtain a low-dimensional self-representation matrix of the hyperspectral image cube; and S15, clustering the obtained low-dimensional self-representation matrix by using a K-means algorithm, so as to obtain an optimal band subset of the hyperspectral image cube.
The present application discloses an optimal neighbor multi-kernel clustering method and system based on a local kernel. The optimal neighbor multi-kernel clustering method based on a local kernel comprises: S11, acquiring a clustering task and target data samples; S12, calculating kernel matrices of views corresponding to the target data samples, and performing centralization and normalization processing on the kernel matrices to obtain a processed kernel matrix; S13, according to the obtained processed kernel matrix, establishing an optimal neighbor multi-kernel clustering objective function based on a local kernel; S14, solving the established objective function in a circulation manner to obtain a dividing matrix after the views are fused; and S15, performing K-means clustering on the obtained dividing matrix to obtain a clustering result.
Disclosed in the present application are a high-order correlation preserved incomplete multi-view subspace clustering method and system. The involved clustering method comprises: S11, inputting an original data matrix, and converting original data into an observed part and an incomplete part; S12, obtaining a plurality of affinity matrices according to self-representation characteristics of the original data; S13, mining a high-order correlation between the plurality of affinity matrices by means of tensor decomposition; S14, learning a unified affinity matrix from the plurality of affinity matrices, so as to obtain a global affinity matrix; S15, constructing a hypergraph on the basis of the global affinity matrix, and constraining an incomplete part of multi-view data by using a hypergraph-induced Laplacian matrix; S16, integrating the global affinity matrix, the tensor decomposition and a hypergraph-induced Laplacian matrix constraint into a unified learning framework, so as to obtain an objective function; S17, solving the obtained objective function by means of an alternating iterative optimization policy, so as to obtain a solution result; and S18, applying spectral clustering to the global affinity matrix according to the obtained solution result, so as to obtain a clustering result.
The present application discloses a double-feature fusion semantic segmentation system and method based on Internet of Things perception. The method comprises the steps of: S1, performing feature encoding on an original image to obtain features of different scales; S2, learning the features of different scales by means of two attention refining blocks to obtain a multi-level fusion feature; S3, performing dimensionality reduction on the multi-level fusion feature to obtain a dimensionality-reduced feature; S4, performing context encoding on the dimensionality-reduced feature by using depthwise factorized convolution of different convolution scales to obtain local features of different scales; S5, performing global pooling on the dimensionality-reduced feature by using a global average pooling layer to obtain a global feature; S6, performing channel splicing fusion on the global feature and the local features to obtain a multi-scale context fusion feature; S7, performing channel splicing fusion on the dimensionality-reduced feature and the multi-scale context fusion feature to obtain a splicing feature; and S8, obtaining an output according to the splicing feature. The semantic difference among multi-level features is relieved, the information representation is enriched, and the recognition precision is improved.
GAESCGAESCGAESCSC, updating parameters of the graph convolutional encoder, parameters of the graph convolutional decoder, and the self-expression coefficient matrix; and S7, converting the finally obtained self-expression coefficient matrix into clustering labels by means of a spectral clustering algorithm. The present application employs joint optimization using reconstruction loss and fusion subspace clustering loss to improve feature quality and clustering performance.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
60.
COLORECTAL CANCER DIGITAL PATHOLOGICAL IMAGE DIFFERENTIATION METHOD AND SYSTEM BASED ON WEAKLY SUPERVISED LEARNING
Disclosed in the present application are a colorectal cancer digital pathological image differentiation method and system based on weakly supervised learning. The colorectal cancer digital pathological image differentiation system based on weakly supervised learning comprises: a collection module, which is used for collecting a colorectal cancer digital pathological image data set; a pre-processing module, which is used for pre-processing data in the collected data set, so as to obtain pre-processed data; a first classification module, which is used for constructing a sampling block differentiation model on the basis of a weakly supervised learning algorithm, and for inputting the pre-processed data into the constructed sampling block differentiation model for processing, so as to obtain a classification result of all pathological image blocks in a full slice sampling package; and a second classification module, which is used for constructing a decision fusion model, and for inputting the obtained classification result of the pathological image blocks into the decision fusion model for fusion processing, so as to obtain a classification result of a full-digital pathological image.
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.
Disclosed is a magnetorheological intelligent fixture for grinding, including a container (1), a water bladder (2), a pressure transmitter (4), a water pump (15), a first electromagnet (8), a controller (10), and an elastic telescopic rod. The elastic telescopic rod is disposed at a bottom of the container (1). Each side wall of the container (1) is provided with the water bladder (2). The water bladders (2) are mutually communicated. The water bladders (2) are respectively communicated with the pressure transmitter (14) and the water pump (15) respectively. The water pump (15) is connected to the water tank (6). A workpiece to be clamped is disposed at a top of the elastic telescopic rod. The container (1) is disposed above the first electromagnet (18). The first electromagnet (8), the pressure transmitter (4), and the water pump (15) are all electrically connected to the controller (10).
B23Q 1/38 - Supports mobiles ou réglables d'outils ou de pièces caractérisés par des particularités de structure concernant la coopération des organes animés d'un mouvement relatifMoyens pour empêcher un déplacement relatif de ces organes utilisant des paliers à fluide ou des supports à coussin de fluide
B24B 49/16 - Appareillage de mesure ou de calibrage pour la commande du mouvement d'avance de l'outil de meulage ou de la pièce à meulerAgencements de l'appareillage d'indication ou de mesure, p. ex. pour indiquer le début de l'opération de meulage tenant compte de la pression de travail
63.
DEEP DELETION CLUSTERING MACHINE LEARNING METHOD AND SYSTEM BASED ON OPTIMAL TRANSMISSION
The present application discloses a deep deletion clustering machine learning method and system based on optimal transmission. The deep deletion clustering machine learning method based on the optimal transmission comprises: S11, obtaining a clustering task and target data samples; S12, dividing each sample in the obtained target data samples into an observable feature part and a deletion feature part, performing initial filling on the deletion feature part on the basis of a filling task, and maintaining the invariance of the observable feature part to obtain a first clustering result; S13, respectively establishing a reconstruction loss and a clustering loss in a neural network structure by means of an optimal transmission distance and KL divergence to obtain an optimized objective function; and S14, fusing the filling task with the clustering task on the basis of the obtained optimized objective function, and filling a deletion value of the deletion feature part to obtain a final clustering result.
Disclosed is a teaching toy with the function of developing a garbage classification ability. The teaching toy comprises a base housing, a rubber sleeve, a garbage bin button and a garbage button, wherein a rectangular snap ring is fixedly mounted on a front face of the base housing, a first clamping groove is formed on an inner side of the rectangular snap ring, a circular snap ring is fixedly mounted on the front face of the base housing, a second clamping groove is formed on an inner side of the circular snap ring, a display screen is fixedly mounted on the front face of the base housing, a control circuit board is fixedly mounted inside the base housing, and a first sensing connector and a second sensing connector are fixedly mounted on a front face of the control circuit board. By means of the teaching toy, a child can learn knowledge related to garbage classification through play, the mode of judging whether classification is correct or wrong by the toy during play is naturally attractive to the child, by means of same a better effect than simply carrying out ordinary teaching is achieved, and the child is enabled to better grasp knowledge of garbage classification. In addition, the garbage bin button and the garbage button can be replaced conveniently, thereby preventing the child from mechanically memorizing button positions, and improving the child's grasping effect.
Disclosed in the present application is a Gaussian mixture model clustering machine learning method under the condition of missing features, the method comprising: S11, acquiring a clustering task and target data samples; S12, dividing each sample in the acquired target data samples into an observable feature portion and a missing feature portion, and initially filling the missing feature portion and keeping the observable feature portion unchanged; S13, selecting representative points of each Gaussian mixture model component by means of random initialization, and establishing, by means of maximum likelihood estimation, an optimization objective function of Gaussian mixture model clustering under the condition of the missing feature portion; and S14, solving, by means of maximum likelihood estimation, the established optimization objective function of Gaussian mixture model clustering, so as to implement clustering. By means of the present application, a filling task is fused with Gaussian mixture model clustering, and missing values are filled under the guidance of clustering results, and the dynamically filled values are then used for Gaussian mixture model clustering.
Disclosed is a late fusion multi-view clustering machine learning method based on a bipartite graph. The method comprises: S11, acquiring a clustering task and a target data sample; S12, performing kernel k-means clustering on each view corresponding to the acquired clustering task and target data sample, so as to obtain a basic division, and calculating diversified regular terms of each view; S13, selecting representative points of each view by using random initialization, and establishing a late fusion multi-view clustering target function based on a bipartite graph; S14, circularly solving the established late fusion multi-view clustering target function based on a bipartite graph to obtain a bipartite graph after view fusion is performed; and S15, performing spectral clustering on the obtained bipartite graph to obtain a clustering result. By means of the present application, optimized representative points can represent information of a single view, and can also better serve view fusion, such that a bipartite graph obtained by means of learning can better fuse information of all views, thereby achieving the purpose of improving a clustering effect.
3 (trifluoromethyl) free radical and electrooxidation to realize the de-aromatization of biphenyl without catalyst. The reaction can occur only under the action of current, which is energy-saving and economical. The free radical used in the reaction is cheap, easy to obtain and low cost. The reaction device is simple and easy to operate, and the yield of the reaction is as high as 60%.
Disclosed is an unsupervised feature selection method based on latent space learning and manifold constraints. The method comprises: S11, inputting an original data matrix, so as to obtain a feature selection model; S12, embedding latent space learning into the feature selection model, so as to obtain a feature selection model with latent space learning; S13, adding a graph Laplacian regularization term into the feature selection model with latent space learning, so as to obtain an objective function; S14, solving the objective function by using an alternating iterative optimization policy; and S15, sorting each feature in the original matrix, and selecting the top k features to obtain an optimal feature subset. In the present application, feature selection is performed in a learned potential latent space, and the space is robust to noise; and the potential latent space is modeled by means of non-negative matrix decomposition of a similar matrix, and the matrix decomposition can clearly reflect a relationship between data instances. In addition, a local manifold structure of an original data space is retained by graph-based manifold constraint terms in the potential latent space.
Disclosed in the present application is a multi-view clustering method based on consistent graph learning, comprising: S11. inputting an original data matrix to obtain a spectral embedding matrix; S12. calculating a similarity graph matrix and a Laplacian matrix according to the spectral embedding matrix; S13. performing spectral clustering on the calculated similarity graph matrix to obtain a spectral embedding characterization; S14. stacking an inner product of the standardized spectral embedding characterization into a third-order tensor, and using low-rank tensor characterization learning to obtain a consistent distance matrix; S15. integrating spectral embedding characterization learning and low-rank tensor characterization learning into a uniform learning framework to obtain a target function; S16. solving the obtained target function by means of an alternate iterative optimization strategy; S17. constructing a consistent similarity graph according to the solve result; and S18. performing spectral clustering on the consistent similarity graph to obtain the clustering result. The present application constructs a consistent similarity graph from a spectral embedding feature for clustering. In this low-dimensional space, noise and redundant information are effectively filtered, and therefore, the obtained similarity graph can well describe a cluster structure of the data.
Disclosed is a deep clustering system based on cross-modal fusion. The system comprises an auto-encoder, a graph auto-encoder, a cross-modal information fusion module and a joint optimization target module, wherein the auto-encoder is used for performing feature extraction on attribute information of graph data and reconstructing an original attribute matrix; the graph auto-encoder is used for performing feature extraction on structure information of the graph data and reconstructing an original adjacency matrix and a weighted attribute matrix; the cross-modal information fusion module is used for integrating modal information of the auto-encoder with modal information of the graph auto-encoder, so as to generate consensus latent embedding, and generating a soft allocation distribution and a target distribution according to the consensus latent embedding and a pre-calculated initialization clustering center; and the joint optimization target module is used for synchronously guiding parameter update processes of the auto-encoder, the graph auto-encoder and the cross-modal information fusion module.
A neighboring subspace division-based hyperspectral imaging band selection method and system. The method comprises: S11. inputting a hyperspectral imaging cube, and calculating a correlation coefficient between any two adjacent bands that the inputted hyperspectral imaging cube comprises to produce a vector of the correlation coefficient; S12. searching for all correlation coefficient extreme points on the basis of the produced vector of the correlation coefficient, filtering out a correlation coefficient minimum point from all of the correlation coefficient extreme points found, determining, by means of the correlation coefficient minimum point filtered out, optimally divided hyperspectral band subspaces; S13. sorting the subspaces on the basis of the size of the number of bands in the subspaces, calculating information entropy of the bands in each subspace, and selecting a required number of characteristic bands from the subspaces on the basis of the information entropy produced by calculation. The method ensures that the final selected band comprises relative intact information.
Disclosed is an unsupervised depth representation learning system based on image translation. The system comprises: an image translation transformation module, which is used for performing random translation transformation on an image and generating an auxiliary label; an image mask module, which is connected to the image translation transformation module, and is used for applying a mask to the image that has been subjected to translation transformation; a deep neural network, which is connected to the image mask module, and is used for predicting an actual auxiliary label of the image to which the mask has been applied and learning a depth representation of the image; a regression loss function module, which is connected to the deep neural network, and is used for updating a parameter of the deep neural network on the basis of a loss function; and a feature extraction module, which is connected to the deep neural network, and is used for extracting a representation of the image. By means of the present application, the problem of it not being possible to process a rotation invariance image by means of an unsupervised method for predicting an image rotation is solved, and the problem of an edge effect being present in an unsupervised method for predicting a geometric transformation is also solved.
mmmm of the auto-encoder, the convolutional auto-encoder and the convolutional variational auto-encoder into a common subspace in an adaptive spatial feature fusion mode, so as to obtain a fused feature Z; the decoder is used for decoding the fusion feature Z by using a structure symmetrical to the encoder, so as to obtain a decoded reconstructed data set (I); and the depth embedded clustering layer is used for clustering the fused feature Z, and obtaining a final accuracy ACC by comparing a clustering result with a real label.
Disclosed is a text-to-image method based on a spectrum normalization stack generative adversarial network. Said method comprises: a first stage: inputting a text into generative adversarial network, and after passing through a conditional enhancement model, splicing a text feature vector corresponding to the text with a noise vector; inputting same into a generator network for processing to obtain a first image; inputting the obtained first image into a discriminator network for down-sampling processing to obtain a tensor corresponding to the first image, splicing the tensor with the text feature vector, and after passing through three parallel convolution layers, outputting a probability value to obtain a low-resolution image; and a second stage: splicing the processed text feature vector processed by the conditional enhancement model with the tensor obtained by performing down-sampling on the low-resolution image generated in the first stage, and inputting same into the generator network for processing to obtain a second image; inputting the obtained second image into the discriminator network for discrimination processing, so as to select a real high-resolution image.
The present invention relates to the field of crop disease resistance breeding, and provides a use of a gene for increasing tomato gray mold resistance. The use of a tomato gene Solyc05g004600 is provided, and the gene Solyc05g004600 is knocked out in the tomato, so that the resistance of the tomato leaf to the gray mold can be effectively increased. Also provided is a method for knocking out a mutant gene Solyc05g004600 in tomatoes.
C12N 15/29 - Gènes codant pour des protéines végétales, p. ex. thaumatine
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/82 - Solanaceae, p. ex. poivron, tabac, pomme de terre, tomate ou aubergine
76.
AMORPHOUS MOTOR AND MANUFACTURING METHOD THEREFOR, AND APPARATUS FOR IMPLEMENTING MANUFACTURING METHOD
Provided are an amorphous motor and a manufacturing method therefor, and an apparatus for implementing the manufacturing method. Magnetic cores (12) are prepared by means of amorphous ribbons; the magnetic cores (12) are arranged in an annular array to form a stator; permanent magnet magnetic poles (10) are arranged in an annular array to form a rotor; stators and rotors are alternately mounted in an axial direction to form an amorphous motor. Amorphous ribbons (22) are prepared by means of single-roller rapid quenching technology, and the length, width, and thickness of the amorphous ribbons are controlled according to target requirements; the amorphous ribbons (22) formed by single-roller rapid quenching and automatic segmentation are further spray-cooled and then automatically stored online; the stored amorphous ribbons (22) are sequentially subjected to alignment, pressing, and heat treatment, and then demolded to prepare the magnetic cores (12). The working procedure is simple, the technical complexity is greatly reduced, automatic flow production is facilitated, and the production cost is remarkably reduced. Amorphous materials can be fully utilized, the material loss in production process of motors is greatly reduced, and the weight of motors having same power is remarkably reduced; moreover, eddy current loss is remarkably reduced, the magnetic circuit is shortened, and the efficiency is improved.
H02K 21/24 - Moteurs synchrones à aimants permanentsGénératrices synchrones à aimants permanents avec des induits fixes et des aimants tournants avec des aimants disposés axialement en face des induits, p. ex. dynamos de bicyclette du type moyeu
H02K 15/02 - Procédés ou appareils spécialement adaptés à la fabrication, l'assemblage, l'entretien ou la réparation des machines dynamo-électriques des corps statoriques ou rotoriques
77.
Streptomyces antioxidans and its use in prevention and treatment of plant diseases
The invention discloses a method and its device for preparing a magnetic core with amorphous ribbon. The magnetic core is prepared with amorphous ribbon, the size of the amorphous ribbon is controlled according to the target requirements, and the magnetic core with required size and shape is prepared according to the target requirements; the single-roller rapid quenching technology with online automatic segmentation and automatic storage capability is used for preparation, which can control the length, width and thickness of the amorphous ribbon according to the target requirements; the amorphous ribbon segmented by single-roller rapid quenching technology is used to spray and cool down one by one, and then air-dry, transfer, spray adhesive and online store it one by one; the stored amorphous ribbon is reshaped, compressed and heat-treated successively, and then demoulded to prepare a magnetic core.
H01F 41/00 - Appareils ou procédés spécialement adaptés à la fabrication ou à l'assemblage des aimants, des inductances ou des transformateursAppareils ou procédés spécialement adaptés à la fabrication des matériaux caractérisés par leurs propriétés magnétiques
H01F 41/02 - Appareils ou procédés spécialement adaptés à la fabrication ou à l'assemblage des aimants, des inductances ou des transformateursAppareils ou procédés spécialement adaptés à la fabrication des matériaux caractérisés par leurs propriétés magnétiques pour la fabrication de noyaux, bobines ou aimants
79.
USE OF GENE FOR NEGATIVELY REGULATING TOMATO LEAF PHOTOSYNTHESIS
Disclosed is the use of a gene for negatively regulating tomato leaf photosynthesis. Knocking out the Solyc05g005230 gene in a tomato can increase photosynthetic efficiency of tomato leaves. The nucleotide sequence of the gene Solyc05g005230 is as shown in SEQ ID NO:1. The content of photosynthetic pigments such as chlorophyll a, chlorophyll b and carotenoids in the Solyc05g005230 gene knockout strain 5230-KO leaves is significantly increased. The main indicators of photosynthesis such as net photosynthetic rate, stomatal conductance and transpiration of the Solyc05g005230 gene knockout strain 5230-KO leaves are significantly increased.
C12N 15/29 - Gènes codant pour des protéines végétales, p. ex. thaumatine
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
C07K 14/415 - Peptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant de végétaux
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/82 - Solanaceae, p. ex. poivron, tabac, pomme de terre, tomate ou aubergine
C12N 15/11 - Fragments d'ADN ou d'ARNLeurs formes modifiées
80.
DEEP-LEARNING-BASED METHOD FOR AUTOMATICALLY READING POINTER INSTRUMENT
A deep-learning-based method for automatically reading a pointer instrument. The method comprises the following steps: S1, inputting an instrument image, which needs to be subjected to detection, into an instrument disk pointer detection model trained by using a convolutional neural network, and performing detection on said instrument image, so as to obtain the position of an instrument disk and the position of a pointer; S2, performing binarization processing on said instrument image, so as to obtain a black and white binarized image; S3, according to the obtained position information of the pointer, cropping the binarized black and white image to obtain a pointer area; and S4, according to the obtained pointer area, obtaining the deviation angle of the pointer, and then obtaining a corresponding degree according to the measuring range of an instrument, thereby realizing the reading of a pointer instrument. An instrument disk and a pointer are detected by means of a deep learning method, the deviation angle of the pointer is obtained by using obtained position information of the instrument disk and the pointer, and the reading of the instrument is then obtained according to the measuring range of the instrument. The accuracy is high, the steps are simple, and the practicability is high.
Provided is a gene Xa7 having high resistance against rice bacterial blight and a use thereof, relating to the field of plant genetics. The nucleotide sequence of the gene Xa7 is shown in SEQ ID NO:1. Also provided is a use of the gene Xa7 having high resistance against rice bacterial blight, which is to improve the resistance of rice against bacterial blight.
C12N 15/29 - Gènes codant pour des protéines végétales, p. ex. thaumatine
C07K 14/415 - Peptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant de végétaux
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/46 - Gramineae ou Poaceae, p. ex. ivraie, riz, blé ou maïs
An application of a gene in enlarging tomato fruits. The size of tomato fruits can be increased by knocking out an IFW1 gene in tomato, so that the yield is increased; and a nucleotide sequence encoded by the gene IFW1 is as shown in SEQ ID NO: 1. Two knockout strains of the IFW1 gene are ifw1-1 and ifw1-2, and IFW1 gene mutation sequences in ifw1-1 and ifw1-2 plants are both SEQ ID NO: 2.
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.
Image encryption and decryption methods based on biological information. The encryption method includes: obtaining the biological information; using the chaotic mapping method to preprocess the biological information to construct the first chaotic biological phase plate and the second chaotic biological phase plate; obtaining the original image to be encrypted and use the first chaotic biological phase plate and the second chaotic biological phase plate to determine the reconstructed optical encrypted image based on the discrete cosine transform method, and Fresnel transform method; and inputting reference light that interferes with the encrypted image of the reproduction light to determine the encrypted image. The invention can reduce the information amount of the key, improve the efficiency of storage and transmission, and improve security.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
344) grown on the foamed nickel still has relatively high specific capacitance at a low temperature, and the assembled supercapacitor can resist low temperature, so that the defective cobaltosic oxide has significant prospects for application.
An ultramarine fluorescent protein, is a protein selected from (a) and (b) protein: (a) a protein consisting of an amino acid sequence set forth in SEQ ID:NO. 2; (b) a protein derived from (a) by substitution, deletion or addition with one or more amino acids in the amino acid sequence of (a) and having activity of the ultramarine fluorescent protein. The ultramarine fluorescent protein (UFP) has the characteristics of pH-insensitivity and light stability, and its chromophore can absorb long-wavelength ultraviolet (UVA) and release fluorescence at wavelength longer than 400 nm. And the aromatic amino acids residue (with content of 9.2%) can absorb medium wavelength ultraviolet (UVB) and release UVA.
A61K 8/64 - ProtéinesPeptidesLeurs dérivés ou produits de dégradation
C12N 9/02 - Oxydoréductases (1.), p. ex. luciférase
C07K 14/435 - Peptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant d'animauxPeptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant d'humains
A61Q 17/04 - Préparations topiques pour faire écran au soleil ou aux radiationsPréparations topiques pour bronzer
C12N 15/70 - Vecteurs ou systèmes d'expression spécialement adaptés à E. coli
87.
MAGNETIC GRINDING APPARATUS AND MAGNETIC GRINDING CONTROL METHOD
The present invention relates to the field of machining. Disclosed are a magnetic grinding apparatus and a magnetic grinding control method. The apparatus comprises: a magnet platform of a ground workpiece fixing table is connected to an electromagnet; the ground workpiece fixing table is used for fixing a workpiece to be ground; an output end of a programmable power supply is connected to a coil of the electromagnet; a permanent magnet grinding rod is located above the workpiece to be ground; a magnetic grinding control system is connected to the programmable power supply; the magnetic grinding control system is used for obtaining a grinding point of the permanent magnet grinding rod on the workpiece to be ground and controlling an output voltage of the programmable power supply by using a removal amount of a blank workpiece surface shape of the workpiece to be ground, the grinding point, and a PWM control method. According to the present invention, the output voltage of the programmable power supply is adjusted by means of the removal amount of the blank workpiece surface shape, the grinding point, and the PWM control method, so as to adjust the magnetic field strength of the electromagnet, and the grinding accuracy is improved by changing the magnetic field strength in real time, fixing the grinding speed and the residence time of the permanent magnet grinding rod.
A magnetorheological intelligent fixture for grinding, comprising a container (1), water bags (2), a pressure transmitter (4), a water pump (15), a first electromagnet (8), a controller (10), and an elastic telescopic rod. A first magnetorheological fluid (12) is contained in the container (1). The elastic telescopic rod is disposed at the bottom of the container (1). The side walls of the container (1) are provided with the water bags (2). The water bags (2) are communicated with each other, and the water bags (2) are respectively connected to the pressure transmitter (4) and the water pump (15). The water pump (15) is connected to the water tank (6). A workpiece to be held is disposed at the top of the elastic telescopic rod. The container (1) is disposed on the first electromagnet (8). The first electromagnet (8), the pressure transmitter (4), and the water pump (15) are all electrically connected to the controller (10). In this way, the water bags and the elastic telescopic rod are used for preliminary positioning and holding of a workpiece, the pressure transmitter is used to measure a clamping force, and then the first magnetorheological fluid solidifies and wraps the workpiece to implement secondary holding of the workpiece to ensure that the workpiece will not be loose and deformed during the holding of the workpiece, and the fixture is suitable for various surface types.
The present invention relates to a personal safety guarantee system and a safety monitoring method. A smart bracelet comprises a detection module, a main chip, a bracelet emergency button and a bracelet wireless connection module, wherein the smart bracelet transmits the detected heart rate, blood pressure and pulse of a human body to a safety monitoring application; the bracelet emergency button is used for receiving first emergency alarm information and transmitting the first emergency alarm information to the main chip; the main chip is further used for transmitting the first emergency alarm information to the safety monitoring application by means of the bracelet wireless connection module; and the safety monitoring application is used for displaying the heart rate, blood pressure and pulse, transmitting a body abnormity alarm signal to a hospital alarm platform, and transmitting the first emergency alarm information to a public security alarm platform. According to the present invention, when a sudden condition of a user occurs, a safety monitoring application sends alarm information to a public security alarm platform, a hospital alarm platform and a mobile phone of an emergency contact in a timely manner, such that the personal safety of the user is monitored and protected in a comprehensive manner.
Provided is the use of the gene LOC_Os05g38680 in increasing the effective tiller number of rice. The nucleotide sequence of the gene LOC_Os05g38680 is as shown in SEQ ID NO:1, and the gene encodes a protein which interacts with MOC1 in rice; and overexpression of the gene LOC_Os05g38680 in rice can increase the effective tiller number of rice.
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/46 - Gramineae ou Poaceae, p. ex. ivraie, riz, blé ou maïs
Provided are a rice grain yield-related gene and an application thereof, the nucleotide sequence of the gene being as shown in SEQ ID NO: 2 or SEQ ID NO: 3. The gene can be used for promoting an increase in rice grain yield, and can also be used for promoting an increase in grain size.
The present invention discloses a food detection and identification method based on deep learning, which realizes food positioning and identification by a deep convolutional network. The method comprises: firstly, training a general multi target positioning network and a classification network by using food pictures; secondly, inputting the results of the positioning network into the classification network; finally, providing a classification result by the classification network. The method uses two deep convolutional networks with different functions to respectively detect and identify the food, which can effectively reduce the labeling cost of the food and improve the accuracy of positioning and identification.
The present disclosure provides a method for increasing lycopene content in a tomato fruit, including knocking out the gene LIE1 of SEQ ID No 1. The disclosure also provides a method for knocking out gene LIE1 in tomato. The method of the disclosure is effective for increasing the content of lycopene in tomato fruits. Finally, the disclosure provides a transgenic tomato plant with knockout of gene LIE1.
A tomato gene Solyc09g005730 and a use thereof, and a method for knocking out the gene in a tomato. A nucleotide sequence of an encoded protein of the gene is shown as SEQ ID NO: 1. By knocking out the gene in the tomato, the lycopene content of the tomato fruit can be increased.
C12N 15/29 - Gènes codant pour des protéines végétales, p. ex. thaumatine
C12N 15/82 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules végétales
A01H 5/00 - Angiospermes, c.-à-d. plantes à fleurs, caractérisées par leurs parties végétalesAngiospermes caractérisées autrement que par leur taxonomie botanique
A01H 6/82 - Solanaceae, p. ex. poivron, tabac, pomme de terre, tomate ou aubergine
A method for improving photosynthesis of rice includes the step of knocking out IPS1 gene in rice. The IPS1 gene has a nucleotide sequence shown in SEQ ID NO: 1.
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