139 results about "Mutation detection" patented technology

The invention relates to the technical field of debugging systems, in particular to an adaptive debugging system and method for touch screen FW parameters, and the system comprises a signal acquisition module, a trend triggering module, a temperature compensation calculation module, a window generation module and a parameter output module. According to the invention, the edge of the driving voltage is carefully collected, the sliding difference algorithm is introduced to filter out high-frequency noise, meanwhile, real-time sampling of environment temperature and baseline capacitance adjustment are combined, the influence of external variables on signals can be dynamically corrected, and accurate judgment of capacitance fluctuation is improved by utilizing periodic delay deviation and regression trend analysis. By means of main frequency feature extraction and zero crossing point sudden change detection, threshold setting can be refined, self-adaptive window expansion can be achieved, touch signal response is kept sensitive and consistent all the time, adjustment and optimization can still be automatically completed even under the condition that the temperature changes frequently or signal interference is complex, parameter drift and debugging failure are effectively prevented, and user experience is improved. And the parameter automatic matching efficiency and the finished product consistency in batch production are improved.

The invention provides a cattle behavior recognition method based on a three-axis attitude angle, and belongs to the technical field of intelligent animal husbandry management. According to the method, three-axis attitude angle signals such as the yaw angle (Yaw), the pitch angle (Pitch) and the roll angle (Roll) of the head of a cattle are collected in real time through a gyroscope sensor arranged in wearable equipment such as a cattle ear tag. The method does not depend on images, accelerometers, microphones or other modalities, only based on attitude angle signals, multiple algorithms such as a time sequence sliding window, frequency domain analysis, weighted scoring, sudden change detection and state transition modeling are utilized, and multiple typical behaviors such as ingestion, rumination, water drinking, bed lying, limping, licking, fright jumping and low activity are recognized. The method is suitable for multiple cattle breeds such as dairy cattle, beef cattle and buffalo, has the advantages of low power consumption, lightweight calculation, low deployment cost, accurate identification and the like, and is convenient for realizing behavior monitoring and health management of large-scale cattle individuals. The algorithm path can be flexibly selected, but a core input signal is only limited to attitude angle data, so that the technical boundary of the patent protection of the method is formed.

The invention belongs to the technical field of power system operation control, and relates to a real-time estimation method and system for comprehensive inertia containing a network construction VSG, a storage medium and electronic equipment, and the method comprises the following steps: S1, constructing a system model; s2, inertia constant state conversion is carried out; s3, mutation detection and correction are carried out; aiming at the problem of real-time evaluation when inertia sudden change occurs in a power system, on the basis of an improved unscented Kalman filtering algorithm, conversion from parameter estimation to real-time state estimation and verification and correction of inertia sudden change conditions are realized, the real-time performance and accuracy of an inertia evaluation result are ensured, and the real-time performance of the power system is improved. And the evaluation method of inertia real-time estimation is enriched.

The invention discloses an underground pipe network water quality sudden change detection system and method. Comprising a multi-parameter distributed sensing network module, a data transmission module, a data processing and analyzing module, a space-time traceability positioning module and a user interaction and alarm module, wherein the multi-parameter distributed sensing network module comprises various types of water quality sensors and hydraulic sensors; the data acquisition module is used for acquiring water quality parameter data and hydraulic parameter data of each node in real time; the invention relates to the technical field of water quality monitoring. According to the underground pipe network water quality abrupt change detection system and method, multi-dimensional data are collected in real time through a distributed anti-interference sensing network, and an intelligent closed loop from data collection to abrupt change recognition is constructed in combination with'mixed transmission architecture + improved Bayesian network fusion analysis + LSTM-AE deep learning detection '; a complex sudden change mode of multi-parameter cooperative change can be rapidly identified, and risk expansion caused by monitoring lag or shallow layer analysis is avoided.

The invention discloses a psychological state dynamic evaluation and early warning system based on multi-modal behavior data, which belongs to the field of medical care informatics and comprises a multi-modal behavior data hierarchical coding module, a time sequence causal atlas construction and reasoning module, a double-stage self-adaptive early warning decision module and a context awareness intervention strategy generation module. A cross-modal association mode is extracted through a double-layer coding mechanism, a time sequence graph containing a causal relationship is constructed, causal reasoning is performed, a double-stage mechanism of short-term mutation detection and long-term trend prediction is adopted to generate graded early warning, and an optimal intervention strategy is selected based on a deep Q network according to a user situation. According to the method, the accuracy, timeliness and intervention effectiveness of psychological health assessment are improved, and dynamic monitoring and early warning of the psychological state are realized.

The invention belongs to the technical field of visual identification, and particularly discloses a thick plate saddle-shaped weld groove feature extraction and size measurement method and system. Comprising the steps that based on multi-scale geometric feature mutation detection, a current frame weld groove three-dimensional point cloud is segmented into a branch pipe face, a groove side wall, a backing weld surface and a main pipe face, and four area three-dimensional point clouds are obtained; according to the three-dimensional point cloud of each area, determining an intersection point of a branch pipe surface and a groove side wall, an intersection point of the groove side wall and a backing welding surface, an intersection point of the backing welding surface and a main pipe surface, an intersection point of the branch pipe surface and the main pipe surface, and a virtual intersection point of the groove side wall and an extension line of the main pipe surface as weld groove feature points; and constructing vectors between the feature points, and calculating the geometric dimension of the weld groove through vector operation. The method is based on multi-scale geometric feature mutation detection and adaptive point cloud segmentation, a fitting curve slope threshold value does not need to be preset, and the method can be adaptive to different included angles between the branch pipes and the main pipe in the pipe tubular joint.

The invention relates to a pig abnormal behavior recognition method based on a three-axis attitude angle, and belongs to the technical field of intelligent breeding and animal behavior monitoring. The method comprises the following steps: acquiring three-axis attitude angle data of a pig, wherein the three-axis attitude angle data comprises a yaw angle, a pitch angle and a roll angle; performing time sequence processing, frequency domain analysis, statistical feature extraction or state sequence modeling on the attitude angle data; and constructing a behavior recognition model, and judging whether an abnormal behavior exists or not. The behavior recognition model may include weighted scoring functions, spectral energy analysis, Z-score mutation detection, or behavior chain modeling based on state transition diagrams. According to the method, multi-dimensional fusion of identification logic is realized, the method is suitable for monitoring various abnormal behaviors of pigs such as oestrus, parturient, fright, rolling and manic-depressive pigs, has the characteristics of low power consumption, simple equipment, extensible algorithm and the like, and is suitable for being deployed in a wearable intelligent terminal of the pigs.

This invention provides a germline mutation detection method and system with a low false positive rate. The system is computer-executed and includes: first, performing a PCR repeat cluster consistency test on sequence alignment files generated from high-throughput sequencing reads, down-regulating the base count weights of inconsistent sites within the cluster; then, based on the sample-specific background error baseline, calculating the variation confidence index of each genomic site using an empirical Bayesian framework to obtain candidate single nucleotide variants (SNPs); obtaining candidate insertion / deletion variants through read clustering and physical verification of insertion fragment lengths; subsequently, performing a dual-engine cross-feedback iteration on the two candidate types until convergence, integrating and filtering, and outputting a structured mutation detection report. This invention significantly reduces the false positive rate of both SNPs and insertion / deletion variants while maintaining sensitivity, and improves the detection capability of complex insertion / deletion variants.

The invention relates to an asynchronous federated learning method and system, and the method comprises the steps: firstly, obtaining the prediction training time of a client through employing an exponential smoothing method in combination with anomaly detection and mutation detection according to the federated learning reality conditions of data isomerism, system isomerism and the like; secondly, utilizing a dynamic threshold segmentation algorithm and Monte Carlo simulation to obtain a two-stage waiting time threshold; and finally, the server selects a local model uploaded by the client to perform parameter aggregation in combination with the training time predicted by the client and a two-stage waiting time threshold, and finally forms a self-adaptive federated learning resource scheduling strategy. According to the method, client node resources can be used to the maximum extent at low cost, the global model training efficiency and precision are improved, and the multi-scene adaptability of federal learning is effectively enhanced. Experimental results show that compared with a classical method, the method has higher accuracy.

The invention discloses a bladder cancer mutation detection and typing method and system using pathomics characteristics, and relates to the technical field of disease detection.The bladder cancer mutation detection and typing method comprises the steps that related data of bladder cancer tissue of a patient is received, and then a bladder cancer tissue pathological section image is subjected to image segmentation to obtain a segmented bladder cancer tissue pathological section image; feature extraction processing is carried out based on the segmented bladder cancer tissue pathological section image to obtain bladder cancer tissue pathological feature data, feature weight weighting processing is carried out based on the bladder cancer tissue pathological feature data to obtain a bladder cancer comprehensive weight coefficient, and the bladder cancer comprehensive weight coefficient is predicted through an ecDNA probability prediction model to obtain an ecDNA probability coefficient; and performing multi-modal space fusion on the ecDNA probability coefficient and bladder cancer tissue gene data to obtain an ecDNA risk score, and finally realizing bladder cancer mutation detection and typing based on the ecDNA risk score.

The application discloses a kind of monitoring variable frequency sampling method, equipment, system and storage medium, the method comprises: obtaining the first sampling data to be detected, first sampling data is that monitoring proxy end is sampled to monitoring object according to set first sampling time interval and obtains first sampling data;According to the operation state of monitoring object, mutation detection is carried out to first sampling data, and mutation detection result is obtained;If it is determined that mutation detection result is mutation, the second sampling data before mutation is obtained, and the second sampling data and first sampling data are sent to monitoring server;Wherein, second sampling data is that monitoring proxy end is sampled in first set time before mutation according to set first sampling time interval and obtains first sampling data, and first set time is determined according to set first sampling data queue length.Therefore, the real-time performance and accuracy of mutation analysis are improved.

A system and method for identifying working medium solidification of a liquid metal heat exchanger comprises a monitoring system, the monitoring system is installed on the liquid metal heat exchanger, temperature and pressure difference information of a working medium inlet and a working medium outlet of the liquid metal heat exchanger is obtained through the monitoring system, and therefore the working medium solidification condition of the liquid metal heat exchanger is confirmed. According to the method, the physical influence of the solidification phenomenon on the heat exchange process in the heat exchanger is combined, multi-area working medium parameters are measured, and judgment logic combining moving average, trend judgment, trend variation analysis and mutation detection is adopted, so that solidification occurrence identification based on multi-physical-parameter dynamic coupling is achieved. And meanwhile, the sudden change detection is adopted, so that the embodiment can respond to the serious rapid solidification phenomenon more rapidly, and the operation safety of the heat exchanger is further improved. According to the identification method, the operation state of the heat exchanger can be monitored in real time, the solidification phenomenon can be captured earlier, and the sensitivity and stability of early warning are both considered.

The application relates to the technical field of gene sequencing data processing and bioinformation analysis, in particular to a Web-based whole-exome sequencing tumor gene mutation detection visual analysis method and system. The system collects user sequencing data and a reference genome version through a Web interactive interface; a program is called to perform quality control cleaning and evaluation on the data, and a visual report is generated; sequence alignment is completed based on the reference genome, and a variation site is identified through algorithm iteration; biological annotation of the variation is combined with a database, a candidate pathogenic mutation set is screened out in multiple levels according to a strategy, the candidate set is projected to a visual interface, a site state is confirmed or removed in response to a manual checking instruction, and a final gene mutation detection report is generated. The application greatly simplifies the whole-exome sequencing data processing procedure, makes it easy for clinical doctors or researchers without bioinformation background to start, and improves the popularization rate and work efficiency of tumor gene detection work.

The application discloses a method for detecting glioma chromosome abnormalities based on targeted sequencing, and belongs to the technical field of biological medicine. The method first acquires the allele frequency of a to-be-detected sample at preset SNP sites (covering 1p, 1q, 19p, 19q, chromosome 7 and chromosome 10), and then calculates and determines whether specific chromosome arms or chromosomes have loss of heterozygosity. Meanwhile, the copy number of the region where each SNP site is located is calculated based on the sequencing depth, and the total copy number of the above-mentioned chromosomes is obtained by integration. Finally, the loss of heterozygosity determination result and the chromosome copy number information are comprehensively combined, so that the simultaneous identification of 1p / 19q co-deletion, gain of chromosome 7 (+7) and deletion of chromosome 10 (-10) is realized. The method does not require paired samples, can accurately quantify the copy number, avoid false positives, and only needs to detect part of the SNP sites, that is, can be combined with hot spot mutation detection, thereby saving cost and improving detection efficiency.

The present application relates to the technical field of gene mutation detection, and particularly relates to a system, method and application for detecting exon skipping mutation.The present application constructs a self-catalytic system based on specific double recognition induction of CRISPR-Cas12a, which is used for sensitive and reliable detection of MET 14 exon skipping mutation of lung cancer patients.The system can effectively release the fluorescence signal through the Cas12a auxiliary cutting, and further realize signal amplification through the self-catalytic mechanism.The present application can solve the technical problems of the existing exon skipping mutation detection system, such as complex detection process, long time consumption, and unsatisfactory detection accuracy.The detection system of the present application has high sensitivity, stability and good reproducibility, and the method has low cost, simple operation, short detection period, good specificity, and low false positive rate and false negative rate.The present application is suitable for clinical sample determination and has an ideal application prospect.

The application provides a primer probe set and a kit for detecting a rifampicin-resistant gene of Mycobacterium tuberculosis, and belongs to the technical field of molecular biology detection.The primer probe set comprises RAA primers and qPCR primers targeting the rpoB gene, probe primers targeting the wild-type rpoB gene, and probe primers targeting the mutant rpoB gene.The application adopts the detection methods of RT-RAA and qPCR in sequence, and the above specific primer probe set can be combined to simultaneously and rapidly detect the 516, 526, 531 and 533 sites of the rpoB gene of Mycobacterium tuberculosis, has good specificity, and the detection sensitivity can reach 5 copies / ul, is 20 times higher than the sensitivity of qPCR (100 copies / ul), and has a 5% detection capability for heterogenic drug resistance mutation; the detection method can also greatly shorten the detection time.

The invention relates to an AKR1C3 enzyme expression level and medical application through KRAS mutation. According to the AKR1C3 enzyme activated anticancer prodrug, KRAS gene mutation can be directly used as a detection target before medication, namely, a KRAS mutation patient is a patient with high expression of the AKR1C3 enzyme and does not need to be subjected to AKR1C3 enzyme expression level or AKR1C3RNA detection, that is to say, KRAS mutation detection positive can be used as a screening index to screen the patient with high expression of the AKR1C3 enzyme.

This invention discloses a primer set for amplifying a novel HCV subtype 6xp and a primer set for detecting drug resistance mutations. The primer set for amplifying the novel HCV subtype 6xp includes nested PCR primers for amplifying the full length of the novel HCV subtype 6xp, while the primer set for detecting drug resistance mutations is a set of primers targeting drug resistance mutation sites in the three functional regions of NS3, NS5A, and NS5B. The primer set provided by this invention has high specificity and high amplification efficiency, enabling specific amplification of the entire genome of the novel HCV subtype 6xp and accurate detection of drug resistance mutation sites in the three functional regions. It is suitable for clinical diagnosis, antiviral treatment guidance, epidemiological surveys, and viral evolution research of this subtype, and has significant clinical application value and scientific research significance.

The application discloses a soil drought monitoring method based on dynamic optimization of multi-source data, relates to the technical field of soil monitoring, and comprises the following steps: delimiting a target region according to a preset rule, and constructing a multi-dimensional drought feature vector by using multi-source observation data. The probability of each cause type is obtained by calculating the Mahalanobis distance between the vector and the preset vector set centroid corresponding to different stress cause types. The same cause probability difference between the target region and the adjacent region is compared. If all the difference values are less than a preset mutation threshold, the soil drought operation path graph is generated by traversing and connecting. If there is a difference value greater than or equal to the threshold, mutation detection and resegmentation are performed on the adjacent region, and the new region corresponding to the minimum probability difference is taken as a new target for iterative calculation, so that the monitoring path is dynamically optimized, the monitoring range and path can be dynamically adjusted according to the regional heterogeneity of drought characteristics, and adaptive tracking and visual operation guidance of the soil humidity condition under complex drought causes are realized.

A system and method for the detection of saliva biomarkers in bodily fluids is described. In particular, the system is suitable for detecting biomarkers of lung cancer in a subject. The system includes an electrochemical sensor chip having at least one well, wherein the at least one well contains a working electrode coated with a conducting polymer functionalized with at least one capture probe, and at least one labeled detector probe. When the at least one labeled detector probe is mixed with a sample of the subject containing a biomarker of lung cancer and added to the at least one well, an electric current is applied to the sample, such that when at least some of the biomarker binds to the capture probe, a measurable change in electric current in the sample is created that is indicative of lung cancer.

Provided are a gene mutation detection method and apparatus, a device, a medium, and a product. The method includes acquiring a suspected mutation site of a nucleic acid sample under test, where the suspected mutation site is determined based on first mutation feature data generated by a first mutation detection module upon mutation calling performed on sequencing data of the nucleic acid sample under test, and the recall at which the first mutation detection module identifies gene mutation sites is greater than or equal to a preset recall; acquiring second mutation feature data and third mutation feature data of each suspected mutation site; and inputting the second mutation feature data and the third mutation feature data into a pre-trained target mutation detection model and outputting a mutation detection result of each suspected mutation site.

The invention relates to the technical field of intelligent information processing, in particular to a text topic sequence mutation detection method based on semi-Markov topic transition, which comprises the following steps of: outputting topic transition probability and residence time distribution by constructing a topic transition model of which the state duration obeys semi-Markov distribution; and identifying high-frequency transition events in a continuous time window by combining multiple signals such as emotional polarity change and text quantity change so as to realize accurate judgment of text theme sequence mutation points. The method solves the problems that in the prior art, the topic transition time sequence modeling capacity is insufficient, the sudden change point judgment mechanism is single, and text topic sequence sudden change recognition is lagged.

Provided are a method and a combination for one-tube simultaneous detection of tumor-specific gene mutation and methylation, and the use thereof. The method comprises searching a database to select mutation and methylation sites of a cancer driver gene and a cancer suppressor gene, synthesizing capture probes correspondingly paired with a target interval, performing hybrid capture on an amplification product of a sample treated with a restriction endonuclease by using a probe set comprising tumor-specific gene mutation and methylation capture probes, constructing a high-throughput sequencing library containing a target region, and performing high-throughput sequencing to obtain the sequence of a target fragment, so as to obtain the results of methylation, point mutations and indel variation of a cancer-associated gene. The provided method enables one-tube simultaneous detection of mutation and methylation states of a cancer-associated gene in one assay, requires a low content of a gene to be detected, can be used for methylation and mutation detection of a tumor-specific DNA, and has low detection costs and high efficiency.

The invention provides a deafness gene mutation cell line, a construction method and a detection quality control product, and belongs to the technical field of gene detection. The invention provides an sgRNA group for constructing a deafness gene mutation cell line, the sgRNA group comprises an sgRNA group designed for mutation sites of deafness genes GJB2, GJB3 and SLC26A4, and 35delG, 176-191del16, 235delC and 299-300delAT which carry the deafness genes GJB2 are obtained through gene editing; 538Cgt in GJB3; t and 547 Ggt; a; in SLC26A4, IVS7-2Agt is added; and extracting genome DNA of the editing cells, and mixing the genome DNA with wild type genome DNA to obtain the deafness gene mutation detection quality control product. The deafness gene mutation detection quality control product provided by the invention can simulate the deafness gene mutation frequency of a real sample, and can more accurately simulate real mutation occurring in vivo.

The present application relates to the technical field of medical artificial intelligence, and more particularly to a respiratory department early warning method based on multi-source data. The content includes: collecting multi-source data of patients with respiratory diseases and preprocessing to obtain single-source data feature vectors, and constructing a single-source data matrix; after weighted processing of the single-source data matrix, splicing is performed to obtain a fusion feature matrix; based on the fusion feature matrix, a trend capturing branch and a mutation detection branch are constructed to obtain a trend feature vector and a residual mutation value vector, and the consistency of the trend and the mutation is quantified to construct a consistency score vector; based on the consistency score vector, the trend feature vector and the residual mutation value vector, a joint feature vector is constructed, and a respiratory disease early warning level is output. The problems of the traditional respiratory department early warning method, such as lack of effective modeling of data timeliness and disease condition correlation, insufficient memory and response ability to high-risk time points, and lack of trend and mutation consistency judgment mechanism, are solved.

The application provides a typhoon path prediction method and system fusing physical constraints and path mutation identification. The method comprises the following steps: obtaining a multidimensional input feature tensor through a feature tensor generation module; performing time modeling through a multiscale modeling module to obtain a deep feature tensor, performing significance guidance through a significance guidance module to obtain a prediction path sequence; identifying a bending angle through a bending event identification module to obtain a plurality of path anomaly scores, introducing a plurality of preset disturbances through a counter disturbance analysis module to determine path confidence, and outputting a path prediction result through a path prediction output module. According to the technical scheme of the embodiment of the application, the typhoon path can be finely modeled, the PINNs physical constraint module is used to ensure that the prediction result meets the physical conservation principle, the bending event identification is used to enhance the path mutation detection capability, the disturbance analysis is used to realize the uncertainty evaluation, and the typhoon path prediction result is more accurate, reliable and physically consistent.

The invention relates to the technical field of biomedical detection, in particular to application of a reagent for detecting LRRK2 gene mutation and cfDNA integrity in preparation of a product for early warning or screening high-risk population of Parkinson's disease. According to the early warning and screening method for the high-risk population with the Parkinson's disease, LRRK2 gene mutation detection of nuclear DNA and plasma nuclear cfDNA integrity analysis are combined, and the accuracy and pertinence of early warning and screening of the high-risk population with the Parkinson's disease are improved through a combined screening method; the sensitivity and the specificity of early recognition of high-risk people with the Parkinson's disease are remarkably improved, the limitation that existing clinical diagnosis of the Parkinson's disease mainly depends on medical history inquiry and physical examination is broken through, and the clinical management burden of the high-risk people with the Parkinson's disease carrying LRRK2 gene mutation is reduced.

The invention relates to a detection strategy of a programmable TMSD-CRISPR system for DNA / RNA (deoxyribonucleic acid / ribonucleic acid) single base mutation. Based on split crRNA and dynamic and thermodynamic regulation and control mechanisms of a dynamic nanotechnology, the purpose of identifying DNA / RNA single-base mutation at different sites is achieved by utilizing different kinetic rates of toehold-mediated strand displacement on strand displacement with a single-base mismatched target strand. According to the present invention, the identification factors for the ssDNA / dsDNA / RNA mutation are significantly enhanced (the ssDNA mutation is 169.4, the dsDNA mutation is 243.8, and the RNA mutation is 156.2), such that the DNA mutation detection with the abundance as low as 0.025% is achieved, and the single base mutation detection is allowed to be performed in the miR-21; in the research of a queue containing 75 clinical samples, the method successfully detects and accurately identifies all KRAS G12V variants at the accuracy rate of 100%, and shows the huge potential of the KRAS G12V variants in clinical molecular diagnosis. The programmable split TMSD-CRISPR has excellent specificity and adjustability, and can be used as a multifunctional platform for biomedical research, molecular diagnosis and precision medicine.

This application discloses an autonomously controlled low-temperature superconducting magnetic gradient readout system and parameter setting method, belonging to the field of geophysical exploration. Before magnetic gradient measurement, the method autonomously sets the SQUID to the optimal operating point based on an adaptive successive optimization algorithm. During measurement, a differential mutation detection algorithm is used to determine in real time whether the system has lost lock and autonomously resets it. If continuous loss of lock occurs, the method autonomously selects the parameter combination of the integrating capacitor and feedback resistor to reduce system sensitivity and relock the measurement. This application solves the problems of tediousness, time consumption, and insufficient accuracy in manually adjusting the optimal operating point of multi-channel readout systems. Simultaneously, by autonomously reducing system sensitivity, it solves the problem of continuous system loss of lock caused by bumps or large magnetic field change rates during dynamic measurements on mobile platforms such as vehicle-mounted, marine, and aerial vehicles. This enables autonomously controlled magnetic gradient measurement under unattended conditions, improving work efficiency and the reliability of magnetic gradient measurement.

The application discloses a nucleic acid absolute quantification method based on nucleic acid constant temperature amplification, which comprises the following specific steps: step one, sample pretreatment, blood samples and saliva samples are pretreated respectively; step two, reaction system configuration and assembly; step three, digital micro-reaction unit preparation and amplification; and step four, multiple signal analysis and absolute quantification. In the application, multiple primer design and a double-probe system are adopted, so that the mutation detection rate is improved, and the detection limit can be reduced to 0.1% variation through Cas12a-sgRNA auxiliary verification. The double-emulsification technology of the micro-fluidic chip is adopted, so that the droplet diameter variation coefficient is controlled within 5%, and the clogged micropore rate is reduced by real-time analysis of the micropore array image through the ImageJ software, automatic marking and exclusion of abnormal units.