97 results about "Nuclear matrix" patented technology

The present invention relates to mammalian expression vectors including nuclear matrix attachment region of human interferon β, and more particularly to pPGM-1, pPGM-2 and pPGM-3 including nuclear matrix attachment region of interferon β gene. Those expression vectors confer position independent expression of the introduced foreign gene, thus increasing the frequency of colonies which efficiently express the recombinant protein.

The invention relates to an inversion method of nuclear magnetic resonance two-dimensional spectrum. The method includes firstly, extracting and estimating noise, namely extracting noise in CPMG (Carr-Purcell-Meiboom-Gill) echo string of acquired data and estimating standard deviation of the noise; secondly, compressing data, namely generating an inversion kernel and performing truncated singular value decomposition and reconstruction by sequence of a nuclear matrix to complete data compression; and thirdly, fitting the data, namely subjecting fitting problem of the compressed data to regularization, performing iterative solution to regularization factors and inversion spectrum by newton method with non-exact one-dimensional search so as to obtain the inversion spectrum. Execution efficiency of two-dimensional inversion algorithm and resolution of two-dimensional spectrum are increased greatly, and the inversion method is well robust.

The invention discloses a semi-automatic image cutting method based on nuclear transfer, which mainly solves the problems that the existing interactive image cutting method can not keep data consistency, the cutting result is not stable, and edges are not clear. The method is realized through the following steps: inputting an image to be cut, obtaining a superpixel set of the input image through a mean shift method, calculating a superpixel color column diagram feature set, building a similarity matrix W through a Bhattacharyya coefficient formula, performing interactive operation on the precut image by a user to obtain a seed superpixel set, building a must-link constrain set M and a cannot-link constrain set C, transferring constrain information M and C to the whole nuclear space through a nuclear transfer method, so as to obtain a nuclear matrix R, clustering the nuclear matrix R through a k mean clustering method, so as to obtain a clustering mark vector, and outputting and displaying a cutting result. The method has the advantages of good data consistency, stable cutting result, simplicity of operation and clear edges, and can be applied to image retrieval, the technology of converting 2D to 3D, target detection and tracking, and medical image analysis.

The invention relates to the technical field of a lithium-ion battery, in particular to water-based conductive ink of the lithium-ion battery. Dry materials mainly comprise (by weight percentage): 0.2-2 percent of water-soluble polymer thickener, 5-25 percent of water-based dispersant, 30-70 percent of conductive carbon black and 20-50 percent of non-polar high polymer water-based latex with the solubility parameter delta less than or equal to 18(J / cm3)1 / 2. The solvent adopts water and accounts for 60-90 percent of the total weight of the pulp. The adhesive properties of the adhesive can be enhanced, the adhesive also has the characteristics of water resistance, NMP (nuclear matrix protein) resistance and electrolyte resistance, a conductive network is formed on a current collector under the effect of the adhesive after adding the conductive carbon black, the contact area between the current collector and a film is increased, and the effect of reducing the contact resistance can be achieved. The current collector after printing of the water-based conductive ink is not only suitable for pulp coating of water-based systems, but also suitable for pulp coating of NMP systems. Moreover, the lithium-ion battery has lower internal resistance and longer cycle life.

The invention discloses a method for processing multi-mode brain nerve image characteristics, and relates to image preprocessing for extracting image characteristics or features of a recognition figure. The method comprises the following steps of: firstly, performing characteristic selection on multi-mode data by adopting a multi-mode nerve image characteristic selection method with sample weightand low rank constraint to obtain a low-dimensional characteristic matrix, calculating a nuclear matrix of each mode to obtain a low-dimensional characteristic matrix, calculating a nuclear matrix ofeach mode, fusing the nuclear matrices of different modes into a nuclear matrix to select more discriminative biomarker characteristics. New Alzheimer disease sample cases are predicted and classifiedby using a multi-core support vector machine. The defects that, in the prior art, a subject can be injured by using biomarker characteristics, an illness brain area of a patient cannot be found by only using one kind of brain image characteristic data or not fully utilizing the multi-mode brain nerve image characteristics, and the characteristics in the used brain image are free of medical explanation are solved.

The invention relates to an electromyographic signal tumble detection method based on a WKFDA. First, surface electromyographic signals are collected from the relevant muscle tissue of the lower limbs of a human body, the action signal segment of the surface electromyographic signals is determined through an energy threshold value, and fuzzy entropy is extracted from the surface electromyographic signals in the action signal segment to serve as characteristics to be classified; then, characteristic sample points are projected to a characteristic space, linear judgment is performed in the characteristic space, and therefore nonlinear discrimination of an original input space can be achieved in an implicit mode. Due to the contribution that corresponding balance weight is adopted for adjusting sample nuclear matrixes, influences of unbalanced data on the classification performance can be overcome. Due to the adoption of the nonlinear mapping, the data processing capacity of a Fisher linear discrimination algorithm based on nucleuses is greatly improved. The experiment result shows that a high tumble mode average recognition rate is achieved through the method, and the recognition result is superior to that of other classification methods.

The invention relates to a multi-instance multi-label scene classification method based on multinuclear fusion. The method comprises the following steps of inputting one multi-instance multi-label data set and splitting into a multi-instance data set and a multi-label data set; using different thresholds to establish a correlation matrix for each package in the multi-instance data set; according to the obtained correlation matrix, calculating a basic nuclear function between each two multi-instance data packages under a same threshold, wherein a basic nuclear function value forms a basic nuclear matrix; carrying out convex combination on element values of a same position in the basic nuclear matrixes under the different thresholds so as to obtain a multinuclear matrix; using the multi-label data set to carry out training so as to obtain a plurality of multinuclear SVM classifiers. The plurality of multinuclear SVM classifiers are used for predicting a label set of an unknown multi-instance data package so as to realize scene classification. By using the multi-instance multi-label scene classification method based on the multinuclear fusion, scene classification accuracy is increased. The invention also relates to a multi-instance multi-label scene classification system based on the multinuclear fusion.

The application provides a three-dimensional gravity field fast and high-precision inversion algorithm in a spherical coordinate system based on a three-dimensional Gauss-legendre numerical integration formula (3D-GLQ). The core content comprises the following two points that the first point lies in the aspect of three-dimensional gravity field forward modeling in the spherical coordinate system,a nuclear matrix equivalent storage strategy is proposed aiming at the problem of low computational efficiency of the traditional 3D-GLQ three-dimensional gravity field forward modeling algorithm, thenuclear matrix equivalence is combined with the existing adaptive splitting strategy, the computational efficiency is increased by two orders of magnitude under the premise of ensuring that the maximum relative error of the forward modeling calculation is less than 0.1%, and the memory occupancy is greatly reduced at the same time; and the second point lies in that the above fast and high-precision forward modeling algorithm is applied to the gravity field three-dimensional inversion, and the gravity field inversion objective function and depth weighting function in the spherical coordinate system are constructed, so that the computational efficiency and credibility of the large-scale gravity field three-dimensional inversion in the spherical coordinate system are greatly improved.

The invention provides a human and mammal cell attachment expression vector. The expression vector contains a nuclear matrix attachment region sequence, wherein the nuclear matrix attachment region sequence is shown as Seq ID No. 1 or is a nucleotide sequence which is homologous with the sequence by over 95 percent. The vector can mediate stable, high-efficiency and lasting expression of exogenous genes in mammal cells, has high safety performance, can be used for gene therapy and has broad market prospect.

The invention relates to an efficient eukaryotic expression vector capable of effectively expressing an antibody and other target proteins and a preparation method and an application thereof, belonging to the technical field of biotechnology. The vector is formed by inserting a nuclear matrix adhering zone, a marmot hepatitis virus post-transcriptional control sequence, a ribosome entry site sequence, a dhfr1-105aa gene segment or a dhfr106-187aa gene segment on a pCI-neo plasmid. According to the invention, the defects that time and energy are wasted when the traditional mammalian cells are expressed and screened and target protein expression level is low are overcome, and a vector transfection CHO (Chinese Hamster Ovary) cell applying the vector can obtain a monoclonal cell strain capable of stably and efficiently expressing antibodies or fusion proteins in a short time, thus the vector provided by the invention has good application value for efficient expression and industrialization of recombinant protein.

The invention relates to a method for recovering a nuclear matrix protein (NMP) solvent in production of a lithium ion battery. The method comprises the following processing steps: (1) absorbing an NMP mixed gas by using a spray absorption tower, preparing an NMP mixed solution with high concentration, pumping and conveying the NMP mixed gas to the spray tower, and conveying NMP crude product liquid to a crude product tank; (2) rectifying and heating the NMP crude product liquid in vacuum to separate water from the NMP, wherein the recovered product is led to a mixing compartment to put into production via a pipeline, so that the NMP is used and recycled over and over again in a reciprocating manner. The water and the NMP are orderly separated in a gaseous form in a heating manner, and purified by in condensing and collecting manners, so as to achieve the target of recovering the product.

A method for evaluating enterprise suppliers based on mixed weight kernel principal component analysis, characterized in that: the method includes the following steps: (1) determining the supplier evaluation criteria, and classifying the output and input indicators; (2) the step ( 1) Take the reciprocal of the obtained input indicators and normalize all indicators using the maximum and minimum method, so that the range is between [0, 1]; (3) Check the normalized data obtained in step (2) Matrix calculation, calculate the averaged kernel space sample kernel matrix and find its eigenvalues ​​and eigenvectors, normalize the eigenvectors, select the eigenvectors with a cumulative contribution rate greater than 80% to form an orthogonal basis matrix; (4) The samples obtained in step (2) are projected, the mixed weight vector is calculated, and the corresponding projection coordinates are weighted and summed; (5) The comprehensive indicators obtained in step (4) are sorted in reverse order. The application of the present invention is applied to enterprise supplier evaluation.

The invention discloses an SAR target identification method based on a Bayes multinuclear learning support vector machine. The objective of the invention is to solve a problem of inaccurate SAR image target identification in the current target identification method. The method comprises following steps of 1) inputting an original SAR image and carrying out preprocessing to calculate nuclear matrixes of different characteristics; 2) according to the multinuclear learning method, combining the nuclear matrixes; 3) establishing a Bayes multinuclear learning support vector machine model for a support vector machine according to the combined nuclear matrixes; 4) using the expectation maximization algorithm to solve the Bayes multinuclear learning support vector machine model to obtain an optimal solution; and 5) using the optimal solution to carry out target identification on SAR image test data. According to the invention, by effectively combining the deduction capability of the Bayes method and the distinguishing capability of the multinuclear learning method, the identification performance is improved and the method can be used for classification of SAR images.

The invention relates to a bicistronic mRNA coexpression gene transporter and a preparation method thereof. The gene order of the gene transporter is SEQ ID No. 15; the gene transporter from 5' end to 3' end comprises bovine Nuclear matrix binding region MAR, artificially constructed combined promoter CAG, Profilin gene FSTN, internal ribosome entry site (IRES), green fluorescent protein AcGFP gene and Rabbit globin poly A signal region; the preparation method comprises the following steps: constructing a carrier pCAG-IRES2-AcGFP1; obtaining FSTN gene and inserting the pCAG-IRES2-AcGFP1 carrier; obtaining the sequence of MAR and inserting the pCAG-IRES2-AcGFP1 carrier; constructing a plasmid carriers so as to obtain the bicistronic mRNA coexpression gene transporter. The gene transporter is not only pure and safe gene transporter but also realizes dual-gene coexpression in any combination, achieves the purpose of multi-gene coexpression through repeated utilization of IRES, and provides new thinking and route for improving the shape of dual or multiple gene control such as economic character.

The method of classifying raw EEG signals uses a classification method based on nuclear features extracted as dominant singular values from an EEG signal segment using singular value decomposition (SVD) and a class means-based minimum distance classifier (CMMDC) to classify a patient's EEG signals. From a mean EEG signal, a set of zero-centered EEG signals are calculated, and from the zero-centered EEG signals and a standard deviation of the EEG signals, a unit variance is calculated for each component. Using the standardized component signals a nuclear matrix is calculated, to which singular value decomposition is applied to generate a set of singular values. The CMMDC is applied to class means associated with first and second classes and a nuclear feature vector to classify the patient's EEG signals as belonging in either the first or second class.

The invention relates to the field of immunoassay medicine, in particular to a nuclear matrix protein 22 chemiluminescent immunodetection reagent kit and a preparing method thereof. The reagent kit can be used in clinic for the early diagnosis and the post-operation therapeutic effect monitoring of bladder cancer. The reagent kit provided by the invention comprises an NMP22 calibrator, a solid-phase carrier pre-coated by an NMP22 monoclonal antibody, an enzyme marker of the NMP22 monoclonal antibody, a chemiluminescent substrate solution acting with the enzyme and a concentrated washing solution. The reagent kit has the advantage that bladder cancer can be simply, conveniently and noninvasively diagnosed in an early phase.

An identifiability face pose recognition method based on local geometrical visual phrase description includes constructing a word bag model on the basis of face local features, introducing space information of words in the word bag model through local geometrical visual phrases, forming feature vectors of images through the geometrical visual phrases, counting the co-occurring feature quantity by aid of inner products of the vectors, forming a training image nuclear matrix through the co-occurring feature quantity, and inputting the training image nuclear matrix into a support vector machine classifier to obtain a face pose classifier through training. The identifiability face pose recognition method can overcome the influence of illumination, shielding and offset on face pose recognition and improves face pose feature identifiability; and improves the calculating efficiency by counting the quantity of co-occurring local geometrical visual phrases in a displacement space, and ensures displacement invariance of space features based on the local geometrical visual phrases.

The invention discloses a remote sensing image change detection method based on nuclear transmission and the method is mainly used for overcoming the defects in the prior art of low detection accuracy caused by a fact that a relation between data cannot be accurately reflected. The remote sensing image change detection method is realized by the following steps of: inputting two remote sensing images with different time phases and making the difference between the two remote sensing images to obtain a difference value image; dividing the difference value image to obtain a super-pixel set; utilizing a k mean value method to divide the super-pixel set into a certain change type, a certain non-change type and an uncertain type; selecting a seed construction constraint set in super-pixels which belong to the certain change type and the certain non-change type; utilizing the constraint set to calculate a seed nuclear matrix and utilizing a nuclear transmission formula to calculate a full-nuclear matrix and opposite angle normalization; and clustering a normalized full-nuclear matrix to obtain a change detection result. The remote sensing image change detection method disclosed by the invention has stronger noise immunity and can be used for effectively removing miscellaneous points; and meanwhile, edge information can be better kept and the accuracy of the detection result is high. The remote sensing image change detection method can be used in fields of urban area extending monitoring, forest and vegetation change monitoring and the like.

The invention discloses a double-loaded core-shell hydrogel, a preparation method and an application thereof. The method includes, firstly, mixing natural polymer with adsorption functional groups anda polyacrylic acid aqueous solution, adding denitrifying bacteria, a nutrient solution and a pH regulator to obtain a core matrix after complete mixing; then adding Ca2+-containing salt and gluconicacid lactone into the nuclear matrix to obtain a mixed solution; secondly, pouring the mixed solution into a mold, dripping a hydrophilic natural polymer solution, and foaming to obtain a porous foaming shell matrix; thirdly, preforming physical crosslinking gelation forming on the porous foamed core-shell matrix to obtain a porous core-shell wet gel; placing the porous core-shell wet gel in deionized water, dialyzing and freeze drying to obtain a single-load core-shell hydrogel; and finally, soaking the single-loaded core-shell hydrogel in nitrobacteria solution and freeze-drying to obtain the double-loaded core-shell hydrogel; The preparation method has simple process operation, no pollution and wide source of raw materials, and the prepared double-loaded core-shell hydrogel has the effect of removing ammonia nitrogen.

The invention is to use a computer vision method to design a target detecting and tracking algorithm, which improves target tracking precision and speed and is suitable for a requirement for intelligently monitoring the storage in a logistics park in real time. In order to improve accuracy and robustness of target tracking, the invention presents a nuclear circulation target tracking method based on an illumination invariant feature for avoiding the shortcoming that the nuclear circulation target tracking is easy to be influenced by illumination variation while only using pixel to compare nuclear-related similarity. The method comprises the steps as follows: calculating a partial sensitive column diagram to an input image firstly; extracting the illumination invariant feature, and then applying a nuclear matrix cycle structure to fast calculate a response confidence map of a target and a template in a frequency domain to obtain the accurate position of the tracked target. The algorithm presented by the invention has relative strong robustness while the illumination is drastically changed and the posture is adjusted.

A strong nuclear matrix binding sequence (MAR) of tobacco and its separating and assay method and application are disclosed. A novel strong MAR sequence is separated from the tobacco genom and has the typical characteristics of MAR sequence and the stronger speicfic binding power with nuclear matrix in vitro. Said MAR sequence can be used to construct plant gene expression vector, that is, antrorsly constructing it at both sides of the gene expression cassette of expression vector pBI121 gus. It can increase the average expression level of exogenous gus gene by 5 times, and used in genetic engineering.

The invention provides a nuclear magnetic resonance echo data inversion method and device based on L0 regularization. According to the method, a nuclear matrix is determined according to nuclear magnetic resonance measurement parameters; an objective function is constructed according to the nuclear matrix by using L0 norms as penalty items of the objective function; an optimal solution of the objective function is determined based on an iteration algorithm; and a nuclear magnetic resonance spectrum of nuclear magnetic resonance echo data inversion is determined according to the optimal solution based on relaxation information. Compared with a traditional nuclear magnetic resonance echo data inversion method, through the inversion method, the L0 norms are used to perform penalty on an inversion result, the effect of a short relaxation component inversion spectrum is improved, the iteration solving process is simple, the robustness of the algorithm is good, and a stable inversion resultcan be obtained under the condition of nuclear magnetic resonance data with different signal-to-noise ratios.

The realization method is part of the biology project technology field, based on sequence alignment nuclear function to forecast signal peptide and its breakpoint position. The invention adopt full sequence alignment to settle the problem that the amino acid sequence lengths are disagreement, and count the relativity between two amino acid sequences to reflect the similarity of both. The new coordinate is made by space transform, after the similarity matrix transform non-negative fix matrix; it settle the problem how make a matrix of dissatisfied non-negative fix condition into a nuclear matrix. For a new amino acid sequence, at its new characteristic space, the said method can forecast whether it is a signal peptide and estimate its breakpoint position. The said invention increase the correctness of forecast signal peptide and forecast breakpoint, so it has a great effect to understand the cause of some illness and is helpful to explore effective cure precept.

The invention provides an electroencephalogram identification method and a device. The electroencephalogram identification method comprises the following steps: firstly, forming a plurality of training sets by repeatedly extracting electroencephalogram samples from an original sample set; introducing a nuclear matrix for calculating a covariance matrix of electroencephalogram, thereby acquiring anaggregation space covariance matrix; decomposing characteristics and constructing a whitening matrix; utilizing the whitening matrix to convert the covariance matrix and performing characteristic decomposition, thereby acquiring a characteristic vector; constructing a space filter through the characteristic vector; extracting the characteristics of each electroencephalogram, thereby acquiring a classification model corresponding to a present training set; utilizing a plurality of classification models to confirm the category of to-be-classified electroencephalogram. According to the invention, the plurality of training sets is formed by repeatedly selecting the training samples, so that the individual difference of electroencephalograms can be effectively restrained and the characteristics with higher discriminability are extracted, so as to increase the recognition rate of electroencephalograms; and meanwhile, the nuclear matrix is introduced when the covariance matrix is calculated,so that the calculated amount can be reduced, the time consumption can be reduced and the treatment efficiency can be increased.

Nuclear matrix proteins (NMP) which are characterized by a defined expression in tissue are provided. These NMPs are useful markers in diagnosing and monitoring the stage of malignancy of a cell and treating cell proliferative disorders associated with the NMP. Also provided are substantially purified polypeptides and nucleotide sequences encoding the NMPs of the invention.

The invention provides an inversion method and a device of two-dimensional nuclear magnetic resonance spectrum based on TwIST. The method includes the steps that through N groups of nuclear magnetic resonance measured parameters, a nuclear matrix is generated, and a target function used for inversion of the two-dimensional nuclear magnetic resonance spectrum is established; when a regularization parameter is evaluated each time, a TwIST algorithm is adopted to find the solution to the target function; according to each solution to the target function, a data ratio corresponding to each solution is determined; according to each data ratio and evaluation of the regularization parameter each time, a curvilinear relationship is established; a slope corresponding to the evaluation of the regularization parameter each time in the curvilinear relationship is calculated, and according to the slope, an optimal evaluation of the regularization parameter is determined; the solution of the targetfunction corresponding to the optimal evaluation is determined, and according to the solution of the target function corresponding to the optimal evaluation, he two-dimensional nuclear magnetic resonance spectrum is generated. In the process of algorithm iteration, the results of the previous two iterations are used to improve the calculation precision, and speed up the convergence of the algorithm.

The invention discloses a magnetic putamen MOFs compound drug-loading system of pillararene nano-valve controlled-release, a preparation method and an application thereof, and belongs to the technicalfield of the compound drug-loading system. The preparation method comprises the following steps: using Fe3O4 as a nuclear matrix, enabling MOFs reaction mother solution to directly react with the nuclear matrix through an in-situ growth mode to form the magnetic putamen MOFs, and modifying 'connecting shaft' molecules on the magnetic putamen MOFs material loaded with the drug through a post-modification mode and performing the follow-up installation of the pillararene nano-valve mediated by a subjective and objective acting force, and realizing the controlled-release under the stimulation oflesion environment factors. Through changing the types of the pillararene nano-valve and the 'connecting shaft' molecules, the slow release of the drugs under the stimulation response can be realized.The whole compound material diagnosis and treatment system is capable of realizing the targeting drug release and the controllable drug release behavior by using the controllability of the nano-valveas the opportunity. The multi-functional point-fixing, timing and positioning treatment can be realized by organically combining the molecular chemistry and the material chemistry, so the disease treatment efficiency is improved.

The invention discloses a three-cistron expression vector, a preparation method and application and belongs to the technical field of gene engineering.The three-cistron expression vector comprises a nuclear matrix combining region sequence and a three-cistron sequence which is formed in the mode that two internal ribosomes enter a site sequence and connected; the structure of the three-cistron sequence is promoter-light chain signal peptide SPL-IRESwt-heavy chain signal peptide SPH-IRESatt-selection marker-Poly A.The vector can express a light chain, a heavy chain and a selection marker gene of an antibody at the same time, the problem that expression of a heavy chain, a light chain and a selection marker gene of a traditional vector is not balanced is solved, antibody quality is improved, and the cloned screening rate of positive cells is raised; meanwhile the nuclear matrix combining region sequence contained on the vector can further overcome transgene silencing, efficient and long-term expression of transgenes in host cells is achieved, on one hand, the antibody protein expression level is improved, and on the other hand, efficiency of screening of subsequent monoclonal antibody cell lines is improved.

The invention discloses a folic acid recognition and pillararene nano-valve controlled-release double-targeted-mediated chemotherapy-photothermal combined cancer therapy compound system, a preparationmethod and application of the compound system, and belongs to the technical field of compound medical materials. The preparation method includes that polypyrrole nanoparticles (PPy NPs) are used as anuclear matrix, a metal organic frame material (MOFs) reaction mother solution directly reacts with the nuclear matrix by means of in-situ growth to form a PPy-MOFs compound nanomaterial, and 'connecting shaft' molecules are modified on the PPy-MOFs compound nanomaterial by means of post-modification for subsequent mounting of a pillararene nano-valve mediated by subject-object acting force; polyethyleneimine polymer (PEI-Fa) modified by folic acid is post-modified on a compound material equipped with a supermolecule nano-valve. Design of the whole compound material therapy system brings synergism of all parts into full play, organic combination of chemotherapy and photothermal therapy is realized, and targeted and controlled drug release is realized through controllability of the nano-valve and folic acid recognition.

The invention relates to test paper for fast detecting carcinoma of urinary bladder. The test paper is combined test paper capable of detecting three kinds of carcinoma of urinary bladder markers, namely, nuclear matrix protein 22 (NMP22), bladder tumor antigens (BTA stat) and carcino-embryonic antigen relevant cell adhesion molecules (CEACAM1) at the same time. The test paper comprises a three-channel bottom plate, a sample adding pad, a gold standard pad, a nitrocellulose membrane and an absorbent paper layer. The three-channel bottom plate is sequentially coated with the sampling pad, the gold standard pad, the nitrocellulose membrane and the absorbent paper layer, and NMP22, BTA, CEACAM1 resisting protein monoclonal gold-labeled antibodies are contained in the gold-labeled pad. The three-channel bottom plate achieves specimen flow division through three fine tubes, and detection of the three kinds of markers is independent from one another. The test paper is fast in detecting, high in sensitivity, high in specificity, good in stability, easy and convenient to operate, visual and reliable in result judgment and easy to master. The test paper can be used for screening of high-risk groups, can also be used for follow-up visiting of carcinoma of urinary bladder postoperative patients, and is very wide in application range.