155 results about "Expression analysis" patented technology

The invention discloses a multi-modal large model identification and intelligent intervention method and system for mental disorder, and belongs to the technical field of intelligent identification and intervention of mental disorder, and the method comprises a multi-modal data acquisition stage, a data preprocessing stage, a feature extraction stage, a cross-modal feature fusion stage, a mental disorder identification stage, and a personalized non-drug intervention stage. In the multi-modal data acquisition stage, skin electricity, electrocardio, electroencephalogram and facial expression multi-modal data are acquired in real time, and a dialogue-feedback-adjustment closed-loop mechanism is constructed in combination with a cognitive behavior therapy theory. According to the multi-modal large model recognition and intelligent intervention method and system for mental disorder, accurate recognition and personalized intervention of mental disorder are achieved by integrating electroencephalogram, electrocardio, skin electricity, expression analysis and text data multi-modal physiological and behavior data and combining a large language model and a cross-modal attention mechanism.

The invention provides a depression virtual reality auxiliary diagnosis and treatment method fused with multi-modal data, and the method comprises the steps: obtaining the multi-modal data, the multi-modal data comprises the peripheral physiological data, such as heart rate, body temperature and skin electricity, monitored by a flexible sensor based on epidermal electrons; and switching to a personalized interactive virtual scene according to the emotional state of the patient in real time, and in the interaction process, obtaining eyeball movement data by the eye movement tracking instrument, and knowing attention distribution, psychological state and micro facial expression change of the user. In combination with multi-modal data of peripheral physiological data, eye movement data and micro-expression change, key features are automatically extracted from multi-modal input data, and emotion analysis and recognition are performed through a multi-modal deep learning method with an attention mechanism. Data can be collected and analyzed in real time, the emotional state of a patient is objectively reflected through the combination of peripheral physiological data and micro-expression analysis, the requirements of the patient are met in a personalized mode, and the treatment effect is improved.

The invention discloses a face feature decoupling representation method and device with causal effect transmission and a medium, and relates to the technical field of causal discovery, image generation and decoupling representation learning. The method comprises the following steps: establishing a variational auto-encoder, and in response to input face data, learning from a potential space based on the variational auto-encoder to obtain potential feature distribution; integrating a structural causal model into the variational auto-encoder, and modeling a causal effect to extract causal features from the potential feature distribution; establishing a graph attention network, inputting the causal features into the graph attention network, and transmitting a causal effect during decoupling; and designing a loss function, and training the graph attention network by using a discriminator. The method can effectively mine and transmit the causal relationship between the face features, improves the explanatory and transferability of feature representation, has high application potential, and is especially suitable for tasks such as face recognition and expression analysis.

The embodiment of the invention provides an ATM withdrawal method and device, electronic equipment, a storage medium and a product, and relates to the field of financial science and technology. The method comprises the steps of obtaining current transaction information corresponding to a bank card, and determining whether a current transaction is an abnormal transaction according to the current transaction information; if the current transaction is the abnormal transaction, determining whether a user of the bank card is a holder of the bank card; if the user of the bank card is the owner of the bank card, micro-expression analysis is carried out on the user, an analysis result is obtained, and if the analysis result indicates that the user is in an abnormal state, micro-expression analysis is carried out on the user again after a first preset duration; the latest analysis result indicates that the user is in an abnormal state or the number of times of micro-expression analysis exceeds the preset number of times; and if the latest analysis result indicates that the user is in the normal state, the current transaction is carried out according to the current transaction information, so that the security of the transaction is greatly improved, and the possibility of misjudgment and false alarm is reduced.

The invention discloses a binuclear internuclear allele expression analysis method and device and a storage medium, and relates to the technical field of bioinformatics transcriptome analysis of binuclear fungi. The method comprises the following steps: respectively carrying out comparative analysis on sequencing data of binuclear fungi and two nuclear reference genomes; performing kernel source classification on each read in the sequencing data by using an SVM model; taking all gene sequences of the kernel 1 as a query set, taking a gene sequence of the kernel 2 as a target set, and constructing a similarity score matrix among the gene sequences by using a BLAST tool; combining the similarity score with gene annotation information, and analyzing and establishing an internuclear allele relationship through a LightGBM model; and generating a counts file, performing FPKM standardization processing, and analyzing the standardized expression quantity in combination with the internuclear allele relationship index to obtain an analysis result. According to the invention, the analysis of the interkaryotic alleles of the binuclear fungi is realized.

The invention discloses an ALS prognosis evaluation system based on UBE2J2 gene methylation and expression level, and relates to the technical field of biomedicine and bioinformatics. Comprising a data acquisition module, a methylation detection module, an expression quantity determination module, a data preprocessing module, a preliminary survival analysis module, a multivariable Cox proportional risk model construction module, an individualized risk index calculation and grouping module and a visualization and clinical application module. By combining UBE2J2 gene methylation and expression quantity analysis, peripheral blood non-invasive detection, standardized experiment and computational analysis process and visual presentation, the method is technically and remarkably superior to the prior art, high accuracy, operability, repeatability and expandability are realized, and the method is suitable for large-scale popularization and application. And the technical defects of single molecular marker, complicated operation, inaccurate prediction and the like in ALS prognosis evaluation in the prior art are overcome.

The invention relates to the technical field of video action detection, and provides a macro-micro expression interval positioning method based on meta-learning, which comprises the following steps: performing face alignment and image size unified processing on an input face expression video frame sequence; performing down-sampling on the processed facial expression video frame sequence based on a pre-trained video understanding model, and extracting time sequence features; dividing and sampling meta-learning tasks according to preset attribute dimensions on the basis of the time sequence characteristics, and constructing a time sequence positioning model at the same time; performing meta-learning training on the time sequence positioning model according to the meta-learning task to obtain a meta-basic model with a generalized spatial-temporal feature representation capability; and carrying out adaptive fine tuning on the element basic model, and using the fine-tuned model to position macro expression and micro expression intervals of the target domain facial expression video. The method can be more easily deployed in various real and complex new scenes, so that the progress of the expression analysis related technology from the laboratory to the practical application is accelerated.

The invention discloses a combined expression positioning and recognition method and device based on aggregation features and double anchoring, and aims at the requirement of single-face fine-grained expression analysis in a first-view video, an end-to-end deep learning framework is constructed, and unified positioning and recognition of macro expressions and micro expressions are achieved. The method comprises the following steps: firstly, extracting multi-scale features and generating an AU code from acquired single face video data through a frame-by-frame AU identification network for aggregating local and global features by combining the advantages of a convolutional neural network and a visual Transform; the spatial-temporal features are fused by using an AU coding-assisted double-flow 3D convolutional network, a multi-scale sliding window strategy and a feature pyramid network are combined, and a double anchoring mechanism is proposed to jointly position an expression interval; and finally, video clips are intercepted based on a positioning result, and classification is completed through an expression positioning and recognition network. Through local-global feature aggregation, a double-flow 3D convolutional network and a double anchoring strategy, the problems of coexistence of multiple expressions in a video, large duration time difference, difficulty in micro-expression detection and the like are effectively solved, and the precision and robustness of expression positioning and recognition are remarkably improved.

The invention provides a gene expression analysis method and device, electronic equipment and a storage medium. The gene expression analysis method comprises the following steps: clustering a plurality of capture sites according to spatial transcriptome data of a target slice to obtain a biological function region; generating a region distribution diagram according to the biological function region and the spatial position information of each capture site; receiving area selection operation to determine a target analysis area; determining a biological gradient direction, and dividing the target analysis region into sub-regions according to the biological gradient direction; according to the spatial transcriptome data, obtaining the region expression quantity of the target gene in each sub-region; performing gene expression analysis according to the biological gradient direction and the region expression quantity corresponding to each sub-region; the gene expression analysis is used for describing the variation trend of the gene expression of the target gene in the target analysis region along the biological gradient direction. According to the embodiment of the invention, gene expression analysis can be carried out in the target analysis area based on the gradient direction.

The invention specifically discloses a salix cheilophila in-situ genetic transformation method independent of a tissue culture system, and belongs to the field of plant genetic engineering. According to the method, semi-lignified branches of salix cheilophila are taken as receptors, vacuumizing treatment is performed by utilizing agrobacterium rhizogenes infection liquid, hairy roots are directly induced under a water culture condition after short-term dark culture, and positive identification is performed through reporter genes. According to the method, tedious sterile tissue culture operation is completely avoided, the transformation period is shortened to about 22 days, and the technical threshold and the time cost are remarkably reduced. By adopting the system, the positive rate can reach 54.33% when the pBI121 vector is used for transformation, and the efficiency is remarkably improved compared with that of an existing method. The method provides an efficient and reliable technical platform for root system gene function research, expression analysis and genetic improvement of salix cheilophila and related species thereof, and has high application potential.

The invention discloses an application of an alfalfa gene MsCBF4 in improving the cold resistance of plants, and belongs to the technical field of gene engineering. In order to excavate a gene with a clear anti-freezing function from medicago sativa, the medicago sativa gene MsCBF4 is successfully cloned, and the expression of the MsCBF4 gene is found to be induced by cold stress and freezing stress through the expression specificity and space-time expression analysis of the gene in the medicago sativa. Besides, a plant overexpression vector containing the alfalfa MsCBF4 gene and recombinant agrobacterium are constructed, transgenic arabidopsis thaliana overexpressing the MsCBF4 gene is obtained through a genetic transformation experiment, freezing tolerance analysis on the transgenic arabidopsis thaliana overexpressing the MsCBF4 gene shows that the overexpression of the MsCBF4 gene enhances the tolerance of the arabidopsis thaliana to freezing stress, and the transgenic arabidopsis thaliana overexpressing the MsCBF4 gene can be used for preventing freezing stress. Therefore, the MsCBF4 gene can be used for improving the cold resistance of the plant.

The invention provides a campus psychological health monitoring and early warning method based on face recognition and expression analysis, and the method specifically comprises the steps: obtaining a face image from a video sequence of a campus environment, employing a YOLO algorithm to detect a small face image of a low-pixel region, extracting the features of the small face image, and improving the detection precision of face recognition; acquiring positions of face key points of the face small images by adopting a face key point detection technology, and adjusting the face small images based on the positions of the key points; aligning and correcting the human face by combining a head posture estimation technology to ensure that each key part can be at a standard position; facial expressions and corresponding psychological states are analyzed through an expression recognition model, expression data and psychological state data are associated, and a campus emotion baseline is established; on the basis of the campus emotion baseline, an Isolation Forest model is adopted to identify potential emotion models and abnormal changes, and alarm reminding is performed through a preset early warning mechanism, so that possible psychological health crises are effectively prevented and coped with, and the physical and psychological health of students is guaranteed.

The present application belongs to the technical field of genetic engineering, and particularly relates to a methyltransferase gene CmCMT2 and CmDRM2 application in regulating chrysanthemum flowering. The present application constructs an RNAi silencing expression vector by isolating CmCMT2 and CmDRM2 genes in a chrysanthemum variety "Jinma", and obtains CmCMT2 -RNAi and CmDRM2 -RNAi transgenic "Jinma" plants by using a genetic transformation method, then performs phenotype observation and statistics on the transgenic plants, and explores CmCMT2 and CmDRM2 the mechanism of the genes affecting early flowering of chrysanthemum by using an RNA-seq method. The CmCMT2 and CmDRM2 genes are cloned from the chrysanthemum variety "Jinma", and spatiotemporal expression analysis shows that CmCMT2 and CmDRM2 the genes are highly expressed during the process of "Jinma" from bud development to color change; and CmCMT2 and CmDRM2 the expression level in leaves gradually decreases during the growth and development of "Jinma". The research results show that CmCMT2 and CmDRM2 the content of GA1 is changed by negatively regulating the expression of CmG20ox2a and CmG20ox2b , so that the flowering period of chrysanthemum is advanced by 15 and 8 days, respectively.

The invention belongs to the technical field of biological detection, and discloses a screening method of respiratory tract infection related biomarkers based on metatranscriptomics. Respiratory tract infection samples with different clinical phenotypes are subjected to metatranscriptome sequencing, data quality control, comparison and transcript quantification, pathogen and host information is reserved, then genes which are stably expressed or remarkably changed in different groups are identified by combining differential expression analysis and co-expression analysis, and potential biomarkers are obtained. And taking an intersection gene of three machine learning algorithms including an LASSO algorithm, a random forest model and an SVM model to obtain the biomarker. The invention provides a biomarker screening method for rapid and accurate identification of respiratory tract infection.

The present application discloses a micro-expression analysis method and system, belonging to the field of computer vision technology. The method includes: obtaining a micro-expression data set and preprocessing it to obtain a target data set; constructing a multi-scale residual channel attention network model, and training and testing the multi-scale residual channel attention network model according to the target data set; inputting the image stream to be analyzed into the tested multi-scale residual channel attention network model for analysis, and outputting the localization data and recognition data of the image stream to be analyzed; processing the localization data and the recognition data to obtain the micro-expression interval of the image stream to be analyzed and the micro-expression category of the micro-expression interval. By comprehensively using the design of the multi-scale shared sub-network and the residual connection channel attention module, the multi-scale residual channel attention network model can provide higher accuracy in the localization and recognition of micro-expressions.

The invention discloses a litchi immunity related gene LcGLO1 as well as an encoding protein and application thereof. A litchi immunity related gene LcGLO1 is separated from litchi, the full-length cDNA of the gene is 1107 bp, and the nucleotide sequence of the gene is shown as SEQ ID NO: 1; the protein coded by the gene is a lipid transfer protein with the full length consisting of 368 amino acids, and the amino acid sequence is shown as SEQ ID NO: 2. Transcription pattern analysis and plant expression analysis find that the LcGLO1 gene can improve the resistance of plants to phytophthora, so that the litchi immune related gene LcGLO1 can be applied to the aspect of improving the disease resistance of the plants or breeding disease-resistant plants.

The invention relates to the technical field of artificial intelligence, and discloses a digital human driving method based on artificial intelligence, comprising the following steps: step 1, acquiring a voice signal, a facial electromyographic signal, a pupil size signal and a hand motion signal of a student through a wearable device, the wearable device comprising a helmet built-in sensor and a hand motion capture device; step 2, converting the voice signal in the step 1 into a fundamental frequency feature vector, converting the facial electromyographic signal into a 28-dimensional muscle activation degree vector, converting the pupil size signal into a diameter change rate scalar, and converting the hand motion signal into a six-degree-of-freedom pose matrix; according to the method, the multi-mode behavior recognition engine is adopted to fuse micro expression analysis, voice stress detection and skeleton motion capture technologies, the technical effect of recognizing the tiny abnormal reaction of the student in real time is achieved, and compared with a visual behavior recognition scheme based on a preset script in the prior art, the defects that deviation correction response is delayed and the safety knowledge memory effect is poor are overcome.

The invention belongs to the technical field of video management, and particularly relates to a video management method based on artificial intelligence. The method comprises the following steps: firstly, extracting an interest value of a user in a video watching process through facial recognition and expression analysis, and judging an attention concentration time frame; and then text features and scene features of the time frame and the advertisement video key frame are extracted, semantic alignment and matching scoring are performed on the video and the advertisement by using a cross-modal matching model, and the advertisement with high matching degree is screened and inserted into the video. The system further collects interaction behavior data generated after the user watches the advertisement, calculates the advertisement adhesion score, dynamically adjusts the advertisement putting strategy, and achieves the continuous optimization of the advertisement effect. The method improves the correlation between the advertisement and the video content and the user experience, and has the advantages of high precision, high adaptability and the like.

The invention relates to the technical field of molecular biology, in particular to a reference gene for Chinese olive functional gene expression analysis and application thereof. According to the invention, the reference gene RPN2B which is most stably expressed in fruits of different varieties (lines) of Chinese olives in different development and maturation periods is screened out, and in addition, two reference genes NIFS1 and RPS16 which are only second to the RPN2B are also screened out, so that the method can be used for expression analysis of nutritional quality or other functional genes of the fruits of the Chinese olives of different varieties (lines) in different development and maturation periods; the specificity, the stability and the accuracy of functional gene expression analysis data are remarkably improved, and powerful support is provided for Chinese olive functional gene expression analysis. The invention also provides a special detection primer for detecting the reference gene of the Chinese olive fruit, and the detection primer can quantify the expression quantity and function analysis of the auxiliary gene through fluorescence in the Chinese olive function research, and has high application value.

The primary culture method of the porcine ovary granular cells comprises the following steps: step 1, taking a fresh porcine ovary, quickly putting the porcine ovary into a Hank's balanced salt solution preheated at 38 DEG C for transportation, repeatedly washing the ovary with the Hank's balanced salt solution to remove blood and impurities, and then extracting follicular fluid with a 5ml syringe under a sterile condition; according to the method, the granular cells can be effectively separated and cultured from the porcine ovary, and the porcine ovary granular cells with higher purity and better activity can be obtained, so that the subsequent cell biology experiment research, such as gene transfection, protein expression analysis and the like, is facilitated; a cell model is provided for researching the physiological functions (such as hormone secretion and follicle development regulation and control) of the porcine ovarian granular cells, the operation is relatively simple, the cost is relatively low, and the used reagents and instruments are common in a cell culture laboratory and are convenient to popularize and apply.

The invention discloses application of a poplar aspartate transaminase gene AspAT10 in regulation and control of plant drought resistance, expression analysis is carried out on a poplar AspATs family gene, it is found that the expression quantity of the poplar AspATs family gene is remarkably induced by drought stress, and a plurality of drought response cis-elements exist in an AspAT promoter region. On the basis, the drought-enduring function of the plant material is verified through phenotype, physiological metabolism and AspAT-transfection overexpression of the plant material. And an important scientific basis is provided for deep understanding of the biological function of AspAT and application of AspAT in drought-resistant breeding of the poplar.

The application belongs to the technical field of biological detection, and discloses a screening method of respiratory tract infection related biomarkers based on macro-transcriptomics. The application performs macro-transcriptome sequencing on respiratory tract infection samples with different clinical phenotypes, performs data quality control, alignment, transcript quantification, retains pathogen and host information, and then identifies genes stably expressed or significantly changed in different groups by combining differential expression analysis and co-expression analysis, obtains potential biomarkers, and obtains the biomarkers by taking the intersection genes of three machine learning algorithms of LASSO algorithm, random forest model and SVM model. The application provides a screening method of biomarkers for rapid and accurate identification of respiratory tract infection.

The invention relates to the technical field of biological medicines, and discloses a construction method and expression application of an Hcp gene deleted strain of a rahnella aqua KCL-5 strain for fish. The Hcp 0186 gene deletion strain is constructed by using a homologous recombination method, the comparison between the deletion strain and a wild strain is carried out, and the result shows that the deletion of the Hcp 0186 gene has an influence on the growth speed, the pathogenicity of the Hcp 0186 gene to the zebra fish is obviously reduced, the survival rate of the infected zebra fish is increased from 0% to 52%, and the Hcp 0186 gene deletion strain can be used as a fish attenuated live vaccine. A recombinant prokaryotic expression vector pET32a-Hcp and expression and purification of fusion protein of the recombinant prokaryotic expression vector pET32a-Hcp are further constructed, and Hcp 0186 rabbit polyclonal antibody serum is prepared as a primary antibody and can be applied to localization expression analysis of fish tissues infected by the bacterium and detection of WB and IHC. Results prove that the Hcp 0186 gene deletion of the strain provides an attenuated strain vaccine and clinical diagnosis and detection application of infected fish of the attenuated strain vaccine, and a scientific basis can be provided for revealing a molecular pathogenic mechanism of the strain and development and application of a mutant strain of the strain.

The invention discloses a mouse primary cardiac endothelial cell extraction method, and belongs to the technical field of biological cell extraction. The method comprises the following steps: step 1, obtaining pure myocardial tissues; 2, the treated heart tissue is transferred into an intelligent tissue grinding system to be ground; step 3, transferring the ground heart tissue into a temperature-controlled enzymolysis reactor, automatically monitoring the digestion process, and terminating the reaction when a preset digestion degree is reached; step 4, carrying out primary cell separation, carrying out magnetic separation by using anti-CD31 magnetic beads, and specifically enriching heart endothelial cells; 5, transferring the purified endothelial cells to an intelligent microenvironment culture system, and automatically optimizing a culture medium replacement period to adapt to a cell metabolism state; and step 6, performing multi-dimensional quality evaluation on the endothelial cells, wherein the multi-dimensional quality evaluation comprises marker expression analysis, in-vitro lumen formation experiment, AI-assisted morphological analysis and digital quality scoring.

The application belongs to the field of plant biotechnology, and particularly relates to a cucumber CsODO1 gene and application thereof, and is a MYB transcription factor capable of being combined with a CsCSE1 promoter, which is screened through a yeast single hybridization. It is proved through EMSA and tobacco transient expression analysis that the CsODO1 gene directly and specifically combines with a "CAACCA" sequence in the CsCSE1 promoter, and inhibits the expression of the CsCSE1 gene. The CsODO1 gene can be induced to express by a powdery mildew fungus, and is differentially expressed in the cucumber infected by the powdery mildew fungus. It is found through a cucumber cotyledon transient transformation system mediated by an agrobacterium that the CsODO1 gene negatively regulates the biosynthesis of lignin and the resistance of the cucumber to the powdery mildew fungus. The application provides a new reference gene resource for the cultivation of a cucumber disease-resistant variety, and provides a new thought for the research on the molecular mechanism of the plant immunity mediated by the lignin pathway.

Disclosed are compositions, methods and kits for determining the presence, absence, amount, copy number, or other characteristics of one or more polynucleotide sequences in two or more samples and use thereof in genotyping, evaluation of copy number variation, expression analysis, determination of splice variants and fusion genes, and other genetic analyses.

The invention discloses a micro-expression analysis method and system, and belongs to the technical field of computer vision. The method comprises the following steps: acquiring and preprocessing a micro-expression data set to obtain a target data set; constructing a multi-scale residual channel attention network model, and training and testing the multi-scale residual channel attention network model according to the target data set; inputting a to-be-analyzed image stream into the tested multi-scale residual channel attention network model for analysis, and outputting positioning data and identification data of the to-be-analyzed image stream; and processing the positioning data and the identification data to obtain a micro-expression interval of the to-be-analyzed image stream and a micro-expression category of the micro-expression interval. The design of comprehensively using a multi-scale shared sub-network and a residual connection channel attention module is adopted, and a multi-scale residual channel attention network model can provide higher accuracy in the aspect of micro-expression positioning and recognition.

The invention discloses a heart failure key gene identification method and system based on a spline regression model and overall entropy change. The method comprises the following steps of: 1, preprocessing data; 2, analyzing time sequence differential expression; 3, constructing a dynamic co-expression network; 4, network overall entropy change analysis; and 5, screening the heart failure key gene. Compared with an existing analysis scheme in which time sequence differential expression analysis and network topology analysis are mutually independent, a coherent technical system from'capturing gene expression time sequence trend 'to'quantifying gene network overall structure evolution' and then'screening key genes' is constructed. The thought jumps out of the limitation of a single method dimension, and more fitting and more systematic analysis of the continuous nonlinear evolution process of the heart failure are realized. Meanwhile, the spline regression model is matched with dynamic network overall entropy change analysis, so that the synergistic effect of effectively screening and comprehensively analyzing differential genes is achieved.

The invention discloses a psychological health service docking method and system based on edge computing, and relates to the technical field of psychological health services. Comprising the steps that intelligent equipment collects face images, psychological health questions and answers and physiological data of docking personnel and transmits the data to an edge unit for real-time processing; the facial image is used for generating a facial heart health coefficient through expression analysis, generating a question heart health coefficient through question and answer data analysis and generating a physiological heart health coefficient through physiological data analysis. According to the method, all coefficients are subjected to information fusion and statistical analysis to obtain a comprehensive heart health value, the comprehensive heart health value is mapped to a psychological health level to generate an individual stage portrait, and dynamic matching of psychological consultants is carried out in combination with historical portrait analysis trends. Comprising a data acquisition module, a facial expression analysis module, a question and answer data analysis module, a physiological data analysis module, a comprehensive heart health calculation module, a stage grading module and a consultant matching module, and psychological health service docking and personalized intervention which are low in delay, high in real-time performance and high in privacy can be achieved.