27results about How to "Low background noise" patented technology

The invention provides a PCB multi-type defect detection method and device based on frequency domain perception enhancement, a storage medium and a program product, and relates to the technical field of computer vision target detection.The method comprises the steps that a to-be-detected PCB image is input into a backbone network for shallow feature extraction, and shallow feature maps of different processing stages are obtained; respectively inputting the shallow feature maps into a multi-domain collaborative feature enhancement network, performing decomposition enhancement on the shallow feature map in each stage through wavelet transform to obtain an enhanced low-frequency component and an enhanced high-frequency component, and performing first reconstruction on the enhanced low-frequency component and the enhanced high-frequency component through first inverse wavelet transform to obtain an enhanced low-frequency component and an enhanced high-frequency component; obtaining a frequency domain enhanced feature map of each stage; inputting the frequency domain enhanced feature map into a neck network, and enabling the neck network to perform multi-scale feature fusion on the frequency domain enhanced feature map to obtain a fused feature map; and inputting the fusion feature map into a prediction output end for target prediction to obtain a PCB defect detection result.

The invention relates to the field of material chemistry on-line detection, in particular to a 1, 2, 4-trichlorobenzene on-line detection material and a preparation method thereof, and provides a film-forming sensitive layer material capable of being coated on the surface of a transducer, and the film-forming sensitive layer material comprises chitosan, a crosslinking component with the content of 0.1-5wt% in terms of glutaraldehyde and magnetic core-shell molecularly imprinted particles after being dried, the magnetic core-shell molecularly imprinted particle contains a ferroferric oxide magnetic inner core, a silicon dioxide middle layer and a molecularly imprinted polymer shell layer, and the shell layer is a cyclodextrin methacrylate and ethylene glycol dimethacrylate copolymer network and takes 1, 2, 4-trichlorobenzene as a template. The material keeps the membrane integrity and long-term stability under the working conditions of circulation and regeneration and also gives consideration to quick response, and the residual 1, 2, 4-trichlorobenzene is controlled to be not greater than 0.10 wt% and the residual glutaraldehyde is controlled to be not greater than 0.5 wt%. The method is used for relieving structural mass transfer contradiction and processing and coating coupling contradiction caused by high filler load, and has online detection application value.

The invention discloses an immunofluorescence imaging method for driving tyramine signal amplification based on chemiluminescence and application thereof, and relates to the technical field of biomedical imaging. The immunofluorescence imaging method comprises the following steps: carrying out first incubation on a to-be-detected sample and a peroxidase-labeled antibody; performing second incubation on the to-be-detected sample after the first incubation and a tyramine substrate containing a fluorophore under a dark condition; adding a chemiluminescent substrate solution into the to-be-detected sample after the second incubation, and carrying out image acquisition; wherein the antibody can be specifically bound with a target protein; the tyramine substrate can generate active free radicals under the catalysis of peroxidase, so that the active free radicals are covalently cross-linked with tyrosine residues; the chemiluminescent substrate solution comprises hydrogen peroxide and luminol. The immunofluorescence imaging method improves imaging signal and fluorescence stability, effectively reduces background interference and phototoxicity, is suitable for long-time stable fluorescence immunoimaging, and is especially suitable for high-sensitivity detection of low-expression protein markers.

The invention relates to a gas chromatograph and a chromatographic analysis method for analyzing sulfides in fuel hydrogen, the gas chromatograph comprises an electronic flow controller, a sample injection valve, a flow path selection valve and a plasma emission detector, two branches are arranged between the sample injection valve and the flow path selection valve, the first branch comprises a chromatographic column I, a cutting valve I and a chromatographic column II which are used for separating H2, CH4S and CS2 from sample gas, the second branch comprises a chromatographic column III, a cutting valve II and a chromatographic column IV which are used for separating fuel hydrogen, H2S and COS from the sample gas, and the plasma emission detector is used for quantitatively detecting CH4S, CS2, H2S and COS which are completely separated. Therefore, operation, use and maintenance are simple, only helium is used as carrier gas, and sensitivity is high.

This application discloses a method, device, and medium for training and applying a geoscientific big data feature extraction model, relating to the fields of geoscientific big data processing and artificial intelligence technology. The method includes: cropping geoscientific modal sample data to obtain several candidate cropping samples corresponding to each geoscientific modal sample data; extracting visual token sequences and text token sequences from the candidate cropping samples and text task prompts; calculating cross-modal entropy based on the visual token sequences and text token sequences, and determining the optimal cropping; inputting the geoscientific modal sample data, the optimal cropping, and the text task prompts into a large language model to obtain sample feature extraction results; and training a trained geoscientific big data feature extraction model using a total loss function, where the total loss function includes the cross-modal entropy based on the candidate cropping samples and the sample feature extraction results. This method avoids the occurrence of feature extraction fragmentation or missed detection problems, and also reduces background interference, thus reducing false positives or false negatives.

The application relates to a gold nanoparticle array preparation method with strong stability and reusability, high cysteamine-stabilized gold nanoparticles are prepared first, the spacing between the gold nanoparticles is changed by utilizing the coulomb repulsion between the gold nanoparticles, then the gold nanoparticle solution is added dropwise to a glass surface modified by gamma-glycidoxypropyltrimethoxysilane to react, stable covalent bonds are formed, and gold nanoparticle arrays with uniform distribution on the glass surface can be obtained after the reaction. The preparation does not require high temperature, the experimental operation is simple and convenient, the gold nanoparticles are arranged in order and closely, have high detection sensitivity, have strong ultraviolet absorption capacity, good stability, reusability, salt resistance and low background interference, and can be reused. The gold nanoparticle array can realize detection analysis on high-salt-content samples in surface-assisted laser desorption ionization mass spectrometry and be used for rapid analysis of small molecule compounds in positive and negative ion dual modes.

The invention relates to the technical field of biomedical detection, and discloses a kit for detecting pancreatic cancer based on a fluorescence labeling method and application of the kit, and the kit is composed of eutectic solvent precursor dispersion liquid containing an interface stabilizer and a polycarboxylate regulator. According to the method, the deep eutectic solvent is driven to be separated out from the water phase by utilizing the strong hydration capability of the polycarboxylate regulator, and the microphase enrichment region with low water content is constructed in situ. In the enrichment area, a compact hydrogen bond network limits free movement of water molecules, and a non-radiative transition channel for transferring excited state energy of fluorescent molecules to a hydroxyl vibration energy level of the water molecules is blocked. The unique microenvironment mechanism significantly reduces the fluorescence quenching effect in an aqueous system, greatly improves the quantum yield and detection sensitivity of the fluorescent probe, and effectively solves the technical problem of weak signal in traditional aqueous phase immunodetection.

The invention discloses a low-background iron-based magnetic resonance contrast agent and a synthesis method and application thereof.According to the low-spinning ferrous iron-based contrast agent, a group capable of breaking bonds through a biological orthogonal catalytic reaction is introduced, amine is generated through biological orthogonal catalytic cracking, obtained aniline is unstable, then 1, 6-elimination occurs in molecules, triazole groups are removed, and the contrast agent is prepared. And then the rest part of the plumbing arm is cracked to finally become a high-spinning ferrous contrast agent. The relaxation rate of the contrast agent is improved through conversion of high and low spin states, low-background activation is achieved, the contrast ratio of magnetic resonance imaging signals is improved, and imaging of a focus area is expected to achieve early detection of serious diseases.

The application discloses a kind of for sweat glucose concentration monitoring method, it is related to sweat monitoring field, comprising the following steps: step 1, enzyme-fixed chain conjugate synthesis: glucose dehydrogenase is reacted with bilirubin oxidase respectively with bifunctional crosslinking agent and is purified, obtain enzyme-crosslinking agent intermediate;It is clicked with azide modified DNA fixed chain chemistry reaction again, and after purification, obtain GDH-fixed chain and BOx-fixed chain conjugate;Step 2, preparation of circular DNA template: after annealing hybridization of phosphorylated template chain and primer chain, it is connected into ring by T4 DNA ligase;Step 3, rolling circle amplification self-assembly package enzyme DNA hydrogel;The present application uses super-flexible DNA hydrogel as flexible electrode material, realizes the efficient fixation and continuous stable catalysis of GDH and BOx, and constructs flexible sweat-based EBFC self-powered sensor as flexible bioelectrode, to realize continuous non-invasive blood glucose monitoring.

The application discloses a two-dimensional Gaussian splash three-dimensional reconstruction method based on multi-model cooperation, and comprises the following steps: acquiring multi-view RGB images, outputting camera parameters and sparse point clouds by using a VGGT model, generating a depth map and a mask map by using a monocular depth estimation network and an image segmentation network, performing dense processing by using a visual shell algorithm, initializing a two-dimensional Gaussian primitive by using the dense point cloud, training the initialized two-dimensional Gaussian primitive, re-rendering depth maps of all views, generating a three-dimensional grid by using a truncated signed distance function and an isosurface extraction algorithm, performing grid optimization on the three-dimensional grid based on local bilateral filtering to obtain a smooth grid, performing scale correction on the smooth grid to obtain a three-dimensional model with a real scale, and generating a comprehensive three-dimensional model with high-fidelity geometry, a real scale and new-view rendering capability through the initialization and optimization strategy based on multi-model cooperation.

The application discloses a highway pavement disease detection method, system and equipment, and relates to the technical field of highway pavement image processing. The technical scheme points are: obtaining a to-be-detected pavement image of a highway; inputting the to-be-detected pavement image into a pre-trained disease area segmentation model for segmentation and extraction to obtain a disease area image of the highway pavement; wherein, a first discriminator and a first generator are used to form a first generative adversarial network, the first generative adversarial network is trained, and when the number of training reaches a maximum number, a disease detection model is obtained; the disease area image is input into the pre-trained disease detection model for detection to obtain a disease detection result of the highway pavement; wherein, a YOLOv8 neural network is trained, and when a first loss function converges, the disease detection model is obtained. The problems that the prior art cannot capture detailed information and has false and missed detection of diseases when detecting pavement diseases are solved.

The invention relates to the field of biotechnology and dead / living cell detection, in particular to a method for rapidly determining the activity of biological membrane cells in immobilized fermentation. According to the method, a methylene blue and trisodium citrate synergistic chromosome system is optimized, a biofilm EPS matrix is synergistically penetrated by virtue of the dispersion effect of trisodium citrate and the reduction characteristic of methylene blue, and a spectrophotometric method is combined to detect the OD value of a staining solution instead of stained cells, so that the efficient quantitative analysis of the ratio of dead cells to living cells of the immobilized biofilm is realized. The method can complete detection within 200 s, is simple and convenient to operate and low in cost, does not need complex equipment, and is remarkably superior to a traditional fluorescent staining method.

The embodiment of the invention provides a goods counting method, electronic equipment and a storage medium. The method comprises the following steps: acquiring an image frame sequence acquired by at least one image acquisition device, and performing vehicle detection according to the image frame sequence to acquire a vehicle detection result; according to a vehicle detection result, extracting a position area of the vehicle in each image frame, and obtaining a vehicle area image; performing illumination influence processing on the vehicle area image, performing cargo instance segmentation processing, and obtaining a cargo segmentation result corresponding to each vehicle; according to the cargo segmentation result corresponding to each vehicle, obtaining a single-frame cargo counting result of each vehicle in each image frame; according to the position information of each vehicle in each image frame, performing position association on the same vehicle, and obtaining track information of each vehicle; and performing time sequence fusion on the track information of the same vehicle and the single-frame cargo counting result to obtain the final cargo quantity corresponding to each vehicle. The goods counting device achieves the effect of improving the goods counting accuracy and stability.

The invention belongs to the field of chemical detection, and discloses a fluorescent probe P1, a preparation method thereof and application of the fluorescent probe P1 in spermidine and viscosity dual-function detection. The structural formula of the fluorescent probe P1 is shown in the specification. The recognition performance of the probe P1 in various common analytes in a DMF-HEPES buffer system is researched through a fluorescence spectrophotometer. Results show that the probe P1 has specific fluorescence recognition performance on spermidine, can overcome interference of other common analytes, and has a wide pH value application range. The probe has relatively good sensitivity on the recognition of spermidine, and the lowest detection limit is 0.213 mu M. In addition, the probe P1 has a good response effect on the viscosity of the solution, is not interfered by the polarity of the solution, and can realize quantitative detection of the viscosity. The results show that the probe P1 has wide application prospects in the fields of food safety, environmental detection and biology.

This utility model discloses an auxiliary device for improving the accuracy of gas chromatography determination of N,N-dimethylformamide in water, belonging to the technical field of N,N-dimethylformamide determination. This auxiliary device includes an auxiliary mechanism and a filtration mechanism. The auxiliary mechanism includes a housing with a door hinged to one side of the upper end via a pair of hinges. A water inlet pipe is installed at the upper end of the door, and a drain pipe is installed at the center of the bottom end of the housing. A limiting frame is installed at the bottom of the housing. The filtration mechanism includes a mounting frame with a pair of equal-dividing plates fixedly installed inside. Slide rails are installed on both sides of the mounting frame at the bottom of the pair of equal-dividing plates. A filter layer and an adsorption layer are slidably installed between the two pairs of slide rails. This utility model can effectively improve the accuracy of gas chromatography determination of N,N-dimethylformamide and has high practical value.

The invention discloses an interpretability method for a decision basis of a medical image classification model, and relates to an interpretability method for a classification model. A channel and a space attention mechanism are introduced in a prototype concept extraction stage, the model is guided to focus on a key semantic region related to a disease, background interference is reduced, and semantic discrimination and stability of a prototype concept vector are remarkably improved; a CARAFE up-sampling method based on content awareness is adopted to replace a traditional up-sampling mode, the problems of edge blur and structure distortion are effectively relieved in the prototype concept vector positioning and deconvolution visualization process, and important anatomical structures and focus contour information in medical images are better reserved; according to the method, semantic suppression of prototype concept vectors in a high-level semantic space is quantitatively analyzed in combination with an anti-fact intervention strategy, contribution of each prototype concept vector to model prediction can be objectively evaluated, and potential error correlation or redundant prototype concept vectors can be revealed, so that the fineness and credibility of model decision interpretation are improved.

The application relates to the technical field of target detection, in particular to a high-altitude electric power operation violation identification method, which discloses the following steps: collecting high-definition images and low-quality images of an electric power operation site by using a drone, and making an electric power site high-definition data set; constructing an image enhancement network based on a local information enhancement module and a global information enhancement module; building a violation identification model based on an improved YOLOv8; selecting a suitable optimizer and a loss function; training and optimizing the constructed model. The optimal model after training and optimization is converted into an RKNN model in the front end, and is deployed to the front end of the drone. Real-time detection is realized by relying on the camera in the front end, and whether the operation personnel violate the rules is judged by the judgment unit according to the detection result. The application provides a high-altitude electric power operation violation identification method, which considers the construction of an operation data set, the enhancement of low-quality images, and simultaneously proposes a violation identification network model based on an improved YOLOv8, so that the accuracy of detection is maximally improved.

The application belongs to the technical field of VOCs detection, and particularly relates to a VOCs component detection system. Sample gas enters an enrichment unit from a sample gas port for enrichment; first carrier gas passes through the enrichment unit after a four-way valve, washes out the gas adsorbed in the enrichment unit, flows into a separation assembly for separation, and then enters a PID detector for detection analysis; after analysis, the carrier gas carrying atomized water and dry carrier gas are used for reverse blowing in sequence, and then the next round of test can be performed. The application adopts a low-heat-capacity chromatographic column and a high-sensitivity PID detector, effectively reduces the volume and energy consumption of the device through EPC control, and effectively improves the applicability of using a portable device to detect a wide spectrum of VOCs; humidification reverse blowing and dry sweeping are set, low-boiling-point species, oxygen-containing VOCs and nitrogen-containing VOCs that are difficult to remove in the traditional way can be effectively removed through humidification reverse blowing, background interference is reduced, and the VOCs detection effect is effectively improved.

This invention discloses an anti-Dabie Banda virus Gn protein nanobody, a bispecific antibody, and their applications, belonging to the field of biodetection technology. This invention constructs an alpaca natural nanobody library, using recombinantly expressed Gn protein as the antigen. Through multiple rounds of gradient screening using phage display technology, three nanobodies—G15, G20, and G40—that specifically bind to the Dabie Banda virus Gn protein are obtained. All three antibodies exhibit excellent antigen-binding specificity and virus-neutralizing activity; among them, G40 shows the most prominent neutralizing effect. The bispecific antibody G40-C1q, constructed based on G40, combines Gn protein and human C1q protein, achieving a synergistic effect of antiviral activity and inhibition of inflammatory damage. It can be used for the development of drugs for the prevention and treatment of Dabie Banda virus infection and for high-specificity detection reagents, providing candidate antibody drugs for the treatment of fever with thrombocytopenia syndrome, and providing a reliable tool for virus-related research, disease diagnosis, and clinical translation.

The present application belongs to the technical field of 3D AOI industrial vision detection, and relates to a fiducial point detection method and device for electronic devices and a readable storage medium. A fiducial point to-be-positioned region image is collected, the fiducial point to-be-positioned region image is detected, and at least one coarse positioning circular region where the fiducial point is located is obtained. Based on the radius of each coarse positioning circular region and the radius of a standard fiducial point, the positioning score of each coarse positioning circular region is calculated. The coarse positioning circular region with a positioning score greater than a preset positioning score threshold is taken as a target coarse positioning circular region. The edge points of the target coarse positioning circular region are extracted multiple times, the edge points extracted each time are fitted, and multiple fitting circles corresponding to the target coarse positioning circular region are obtained. The difference between the radius of each fitting circle and the radius of the standard fiducial point is calculated, the fitting circle with the smallest difference is taken as the best fitting circle, and thus the fiducial point of the electronic device is obtained, effectively improving the detection precision and detection efficiency of the fiducial point.

The invention discloses a nucleic acid in-situ detection system based on CRISPR / dCas fusion protein and TSA signal amplification and application of the nucleic acid in-situ detection system based on CRISPR / dCas fusion protein and TSA signal amplification, and the nucleic acid in-situ detection system based on CRISPR / dCas fusion protein and TSA signal amplification comprises fusion protein based on a CRISPR / dCas system and a tyramine solution modified by a fluorophore, the fusion protein based on the CRISPR / dCas system is at least one of the following components: dCas9-HRP or biotinylated dCas9-Avi Tag, dCas9-HRP, dCas9-Avi Tag, dCas9-HRP and dCas9-Avi Wherein the dCas9-HRP has a sequence as shown in SEQ ID NO: 1 or a functional variant of the sequence as shown in SEQ ID NO: 1; the biotinylated dCas9-Avi Tag has a sequence as shown in SEQ ID NO: 2 or a functional variant of the biotinylated dCas9-Avi Tag.

The application provides a ventilator internal gas path microorganism microfluidic enrichment and rapid detection system, and belongs to the technical field of ventilators. The system comprises a gas path sampling module, which is used for obtaining gas path sample information; a microfluidic enrichment module, which is used for outputting corresponding enrichment detection signals; a signal preprocessing module, which is used for generating microorganism state data of a target ventilator internal gas path; a multi-parameter data acquisition module, which is used for constructing a microorganism concentration feature data set; a gas path microorganism analysis module, which is used for obtaining a microorganism pollution state coefficient of the target ventilator through comprehensive calculation, and constructing a gas path risk situation coefficient of the target ventilator based on the microorganism pollution state coefficient of the target ventilator; and a microorganism risk analysis module, which is used for calculating a microorganism risk evaluation coefficient of the target ventilator. The application can improve the operation safety and stability of the ventilator.

The application discloses a table document comparison and recognition method and device, and the method comprises the following steps: positioning a paper table document to be compared through a table document positioning model, optimizing the background of the image to be compared through a table image enhancement model, obtaining a table region picture through a table detection model, recognizing the table region picture by using a table structure recognition model and a character recognition model, and finally sending the recognition result into a difference comparison model to output the comparison and recognition result of the table cells and characters; the paper table document and the electronic table document having a corresponding relationship are extracted for text content and table structure, the difference between the table content is recognized, and the table document is automatically audited, so that the efficiency of the table document auditing can be improved and the auditing cost can be reduced.

The application discloses a coumarin-quinoline hybrid near-infrared fluorescent probe compound for reversibly detecting sulfur dioxide and hydrogen peroxide, a synthesis method and application thereof. The probe takes a coumarin derivative as a fluorescent group and is connected with a quinoline salt through a conjugated chain. The probe itself has weak fluorescence, and after a specific Michael addition reaction occurs between the C-4 position of the quinoline salt unit of the probe and HSO3-, strong near-infrared fluorescence emission is generated at 712 nm, the response time is less than 5 seconds, and the detection limit is as low as 15.5 nM. The addition product can be oxidized by H2O2, the original probe structure is restored, and the fluorescence is quenched, so that reversible detection is realized. The probe has high selectivity and strong anti-interference ability. The probe can be used for quantitatively detecting the content of sulfur dioxide in food and water samples, and is successfully applied to imaging of endogenous and exogenous sulfur dioxide in living cells, monitoring of sulfur dioxide in lipid droplets and reversible cycle imaging of sulfur dioxide and hydrogen peroxide, and has important application value in the fields of food safety monitoring and biomedical research.

This invention relates to a YOLOv11 cross-stage, multi-scale pest detection method for high-density adult insect images, belonging to the field of pest detection technology. The purpose of this invention is to address the problem of poor detection accuracy when using existing models to detect various types of adult insects. An improved AMC-YOLO model, after training, predicts all adult insect categories and bounding boxes in the image; based on all adult insect categories and bounding boxes, the number of each type of adult insect is obtained, thus achieving pest detection. The improved AMC-YOLO model is based on the YOLOv11 baseline model. It replaces the Conv module, which has a downsampling function in the YOLOv11 model, with the Adown downsampling module. A GSFM global semantic fusion module is constructed in the neck network of the YOLOv11 model. The GSFM global semantic fusion module performs cross-stage fusion of the localization features output from the backbone network and the semantic features output from the neck network of the YOLOv11 model. Finally, the C3k2 module at the end of the backbone network and the C3k2 module at the end of the neck network of the YOLOv11 model are replaced with the C3k2_MSGConv multi-scale grouped convolution module. This invention is used for the accurate detection of pests.

This application provides a method, apparatus, and electronic device for generating an insulator mask, relating to the field of image processing technology. It addresses the problems of poor adaptability of traditional image segmentation methods to complex insulator shapes and susceptibility to background interference. The method includes: determining an oriented bounding box of the region containing the insulator based on a target image containing the insulator; determining a preliminary segmentation mask of the insulator based on the region contained within the oriented bounding box; determining the width values ​​corresponding to multiple vertical coordinates of the preliminary segmentation mask along a first direction, where the first direction is parallel to the long side of the oriented bounding box; determining the coordinates of the center point of the effective region of the preliminary segmentation mask in the row corresponding to each width value based on each width value and the coordinates of the sampling points contained in the row corresponding to that width value; obtaining the axis equation representing the principal axis of the insulator by fitting the coordinates of each center point; and generating the mask of the insulator based on each width value and the axis equation.

This invention relates to the fields of molecular biology and biotechnology, and provides a reporter vector for visualizing small RNA-target gene regulation. Using a pCOX2 vector as a backbone, it carries a CaMV 35S promoter, a RUBY reporter gene, and the target site sequence of a small RNA target gene, forming a cis-35S-RUBY-target site expression cassette. The CaMV 35S promoter is effectively linked to and drives the expression of the RUBY reporter gene, and the target site sequence is located downstream of the RUBY reporter gene sequence. This invention also provides a method for constructing and applying the aforementioned reporter vector. By constructing a dedicated reporter vector carrying the RUBY reporter gene and combining it with the target site sequence of a small RNA target gene, this invention achieves visual verification of the regulatory effects between small RNA and target genes, offering advantages such as ease of operation, intuitiveness, high efficiency, non-invasiveness, and low cost.