22 results about "Research model" patented technology

The invention discloses a root canal isthmus 3D printing research model construction method and device, a medium and a product, and relates to the technical field of root canal isthmus printing.The method comprises the steps that root canal original data and prepared root canal data are obtained; the root canal original data are screened various typical form data containing root canal isthmus; obtaining expanded main root canal diameter data according to the prepared root canal data, extracting original tooth root three-dimensional surface data according to the root canal original data, and combining the original tooth root three-dimensional surface data with the expanded main root canal diameter data to obtain a root canal isthmus 3D printing research model. The root canal original data screened out in the application contain all possibilities of the root canal isthmus, and compared with a modular stacking mode in the prior art, a mode of carrying out layer-by-layer modeling by utilizing the root canal original data obtained by scanning in the application can more accurately simulate the shape and size of the real root canal isthmus.

The invention belongs to the technical field of biomedicine, and particularly relates to an animal model and a modeling method thereof. According to the method, the northwest dryness syndrome type sub-health animal model is successfully constructed, an open model evaluation mode is adopted, and the established model is evaluated through goodness of fit; furthermore, autumn pear syrup is used for indicating that the prescription corresponds to the syndrome. The northwest dryness syndrome type sub-health target model established by the invention can provide a stable and reliable research model for external dryness syndrome essence exploration, arid region sub-health prevention and treatment, drug effect and pharmacological mechanism research of traditional Chinese medicines, prescriptions and the like with body resistance strengthening and dryness moistening effects, health product research and development and the like. An open model evaluation mode is adopted, and the higher the goodness of fit is, the closer the model to the northwest dryness syndrome type sub-health target model is. The northwest dryness syndrome type square domain dryness evil sub-health rat model is more suitable for arid region sub-health status research, and the northwest dryness syndrome type autumn cause dryness evil sub-health rat model is more suitable for autumn moistening health care research.

The present invention proposes an optimization method for two-shift multi-task scheduling considering processing asynchronous speeds. Taking two-shift multi-task processing as the research object, it considers the actual problem of the impact of workpiece switching between different shifts on production goals. By establishing a model for workpiece switching, it studies two-shift multi-task scheduling with additional switching costs for different shifts with different processing speeds, analyzes the relationship between the switching costs of workpiece switching and shifts, designs a pseudo-polynomial time dynamic programming algorithm, and obtains a multi-task scheduling decision plan. The present invention is oriented to production practice, aiming to provide a theoretical basis for enterprises to coordinate the optimization decision of multi-task scheduling in the two-shift working system, and also provide a research model for reference for other types of working modes such as three-shift systems.

The present invention discloses a model test system for studying critical conditions for instability of a vegetated slope under rainfall, wherein a vegetated slope model is provided in a centrifugal environment double-layer seepage model box; a graded rainfall feedback simulation system simulates the requirements of specific rainfall intensity and duration, and induces changes in the internal moisture field conditions of the vegetated slope model; an artificial root strain analysis system simulates the physical soil consolidation effect of the root system on the slope surface and the regulating effect of matrix suction; a high-speed camera system for slope surface cracks records the entire rainwater infiltration and slope surface scouring of the test slope, and clearly captures the entire process of development, extension and penetration of slope surface cracks; a rock and soil moisture content monitoring system realizes the response of the slope moisture field in real time under different rainfall and artificial root working conditions. The present invention is used to carry out model tests for studying critical conditions for instability of a vegetated slope under rainfall conditions, and provides an effective testing means for evaluating the influence of vegetation on slope stability under rainfall conditions.

The present application relates to the field of aquaculture technology, and particularly relates to a culture method of bigmouth bass gill explants and application. The present application provides a culture method of bigmouth bass gill explants, which uses explant culture solution to culture the gill explants of bigmouth bass. The explant culture solution is formed by adding fetal bovine serum, fish serum, trinity, D-galactose, L-alanyl-L-glutamine, sodium pyruvate and melatonin into a basic culture medium. In combination with dynamic culture conditions, the natural three-dimensional structure and intercellular connection of the gill tissue can be preserved, and the metabolic activity and functional integrity thereof can be maintained. The present application can solve the technical problem that the prior art cannot provide an ideal research model which can both maintain the structural integrity of the gill tissue and accurately reflect the functional characteristics of the gill tissue. Through the culture method, research models such as ammonia nitrogen stress can be efficiently constructed, thereby providing technical support for the research of bigmouth bass gill tissue physiological mechanism, disease prevention and control, environmental risk assessment and the like.

The present invention proposes an optimization method for two-shift multi-task scheduling considering switching time, taking two-shift multi-task processing as the research object and considering the actual problem of the impact of workpiece switching between different shifts on production objectives. By establishing a workpiece switching model, analyzing the relationship between the switching time of workpiece switching and shifts, designing a pseudo-polynomial time dynamic programming algorithm, a multi-task scheduling decision scheme is obtained. The present invention is oriented to production practice, aiming to provide a theoretical basis for enterprises to coordinate the optimization decision of multi-task scheduling under the two-shift working system, and also provide a research model for reference for working modes such as three-shift.

1. Name of the product of this design: Texture Analyzer for Physical Property Testing (Scientific Research Model). 2. Use of the product of this design: The instrument is used to obtain physical property indexes of samples such as hardness, crispness, elasticity, ductility, resilience, etc. by measuring the reaction force received by the probe during the process of applying external force to the sample and combining time and distance. 3. Design key points of the product of this design: Lies in the shape. 4. Picture or photograph that best shows the design key points: Front view.

The invention belongs to the technical field of animal model construction, and discloses a construction method and application of a mouse encephaledema model. The construction method of the encephaledema model is simple and convenient to operate, simple and easy to repeat, stable in injury, high in success rate and low in death rate, and the encephaledema model can be obtained only by applying 0.4-0.6 W ultrasonic stimulation to the brain of an animal. Parameters can be adjusted according to actual needs, so that the damage degree is changed, the research purpose is met, and high controllability is achieved. The construction method provides a new research model for in-vivo research of the occurrence and development process and mechanism of encephaledema.

The present invention provides a data-driven causal tracing method, system, storage medium and electronic device for automobile attribute opinion, which relates to the field of data processing technology. The data-driven causal tracing method for automobile attribute opinion proposed in the present invention includes two aspects: a method for constructing an automobile attribute hierarchical network and a method for tracing the causal relationship of automobile attribute opinion. It only needs to use the total text of social comments on the automobile to be analyzed, without tracing the massive text corpus, which effectively solves the problems of low coverage and strong dependence on text corpus in the existing research model; and on the basis of traditional attribute opinion mining technology, it explores the correlation between opinions in the attribute hierarchy, realizes opinion causal relationship tracing, and helps enterprises to comprehensively, quickly, accurately and efficiently discover the deep-seated reasons for user opinions, better grasp the advantages and disadvantages of automobile attributes, understand user needs, and formulate more accurate product improvement strategies.

The invention relates to a construction method and application of an IgA nephropathy animal model, and belongs to the technical field of biology. The construction method comprises the step of injecting an effective dose of antisense gamma PNA capable of targeting an animal C1GALT1 gene into an experimental animal through veins. The method is easy and convenient to operate and high in modeling success rate, and a research model is provided for exploring IgA nephropathy occurrence and related mechanisms.

The invention discloses establishment and application of a humpback perch frontal bone tissue osteoblast line, and relates to the technical field of biology. The cell line is a humpback perch frontal bone tissue osteoblast line CAFBOB, the preservation number is CCTCC NO: C2025129, and the cell line is derived from a humpback perch juvenile fish frontal bone tissue and is established after tissue separation, primary culture by a dry pasting method, subculture and cryopreservation resuscitation. The biological characteristics are stable, 1-40 generations are mainly long fusiform, the chromosome karyotype is 2n = 48, strong alkaline phosphatase activity is achieved, the transfection efficiency is about 85%, and the activity is good after cryopreservation and resuscitation. The establishment method is high in repeatability, the obtained cell line can be used as an in-vitro research model and applied to morphological specialization mechanism analysis, osteogenesis-related gene function verification, classification dispute solution and seeding process research of the humpback perch, the blank of the bone tissue cell line of the humpback perch is filled, and the bone tissue cell line has important scientific research value and application prospect.

The invention provides a testing method and device for a large investment research model, computing equipment and a storage medium. The method comprises the following steps: generating a plurality of pairs consisting of expected questions and expected answer results based on an investment research corpus; based on the multiple pairs, the recall ability of the investment and research big model is determined, and the recall ability represents the accuracy of an answer result returned by the investment and research big model for the expected question relative to the expected answer result; inputting a query related to at least one theme in the plurality of different themes into the investment research large model to obtain a plurality of generated answer results; on the basis of the multiple generated answer results, the generation capacity of the large investment research model is determined, the generation capacity depends on the capacity on multiple generation dimensions, and the multiple generation dimensions at least comprise the data accuracy and the data logicality of the generated answer results; and based on the recall capability of the investment research large-scale model and the generation capability of the investment research large-scale model, obtaining a test result of the investment research large-scale model.

The application relates to an improved DS evidence theory method based on a liver disease consultation research model, which comprises the following steps: first, establishing a dispute table and a dialogue tree model for consultation, creating a recognition framework, and obtaining initial evaluation values of each node and rule relations and corresponding strengths between the nodes; obtaining evaluation values of each evidence node for a conclusion node according to a CEM matrix; in a fusion process, calculating Pignistic probability distances and conflict coefficients and synthesizing the conflict distances, and scaling the distances by considering conflict consistency degrees between evidence sources during the synthesis; second, calculating the credibility of each evidence source; and finally, weighting and averaging the evidence sources according to the credibility of each node to correct and fuse the evidence sources by using a traditional DS evidence combination rule to obtain final evaluation values of the nodes. In an example, the method can effectively solve the conflict problem without changing the DS combination rule, and has good anti-interference ability and convergence.

This invention provides a method and system for the transformation of scientific research results based on a large-scale research model of birth defects in children. It relates to the field of computer application technology within bioinformatics. The method involves performing correlation mapping on input research data on birth defects, generating a cross-data source data correlation network using the large-scale research model, and performing research discovery mining processing accordingly. This generates a package of research discovery mining results, which are then screened for transformation potential. A transformation potential screening report is generated by combining relevant biological knowledge bases and clinical translation rules. Based on the transformation goals that meet the screening criteria, a scientific research result transformation plan is generated. Finally, a scientific research result transformation implementation link is established based on the transformation plan, generating a transformation implementation plan and matching transformation tasks with clinical research institutions and scientific validation platforms. This ensures the smooth implementation of scientific research result transformation and improves transformation efficiency and success rate.

The application comprises a RAS gene cluster-based pediatric AML prognosis model construction method, which relates to the cross field of bioinformatics and medical technology. It comprises: S1: data acquisition and integration, standardization and integration processing of expression data; S2: sample typing, obtaining at least two subtypes with different prognoses; S3: prognosis model construction; S4: clinical correlation verification, constructing a visual prognosis evaluation system integrating risk stratification and clinical characteristics; S5: immune infiltration correlation verification, establishing the correlation between risk stratification and immune infiltration characteristics; S6: drug sensitivity correlation verification, determining the correlation between risk stratification and drug sensitivity; S7: key gene verification. The application realizes the precise risk stratification of pediatric AML patients by integrating RAS signal pathway gene characteristics and clinical data, and the prognosis model is verified by training set and verification set, which provides a standardized scientific research model framework and reliable data support, and provides an efficient auxiliary tool for pediatric AML related scientific research.

The invention relates to the technical field of GIS pipe bus flange monitoring, and discloses a multi-source fusion GIS pipe bus flange integrated monitoring method, system, device and medium, and the method comprises the steps: obtaining the multi-source operation monitoring data of a target GIS pipe bus flange, building a monitoring research model based on the multi-source operation monitoring data, and carrying out the multi-source operation monitoring data of the target GIS pipe bus flange; taking the monitoring research model as an intelligent agent, establishing a multi-source information fusion decision framework based on the intelligent agent, constructing a fusion algorithm, performing feature extraction and state judgment on the multi-source information fusion decision framework, and obtaining a comprehensive health state evaluation result of the GIS tubular bus flange. And the operation state of the GIS tubular bus flange can be comprehensively reflected. By establishing a multi-source information fusion decision framework and an optimal state recognition model, deep integration and analysis of multi-source data are realized, associated information among the data is mined, and the reliability and practicability of a monitoring result are improved.

The embodiment of the invention belongs to the technical field of Internet, and relates to a big language model-based operational research model recommendation method, which comprises the following steps of: obtaining text information input in a model recommendation interface by a target user; identifying the text information, and determining model demand information corresponding to the target user; converting the model demand information into a corresponding target high-dimensional vector; performing retrieval in a preset vector database according to the target high-dimensional vector, and determining a recommended operational research model; and displaying the recommended operational research model on the model recommendation interface. The invention further provides an operational research model recommendation system based on the large language model, computer equipment and a storage medium. According to the method, deep understanding is carried out on the demand through the large language model, the user demand can be better matched with the corresponding operational research model, the problem of human intervention or large errors in a traditional recommendation method is avoided, and therefore the result accuracy is improved.

The invention provides a traditional Chinese medicine preparation process knowledge representation learning research model embedded with a time dimension, and aims to solve the complex time sequence dependence problem and the multi-source heterogeneous data integration problem in the traditional Chinese medicine preparation process. According to the model, a time sequence knowledge graph with time information is constructed, and the time dependency relationship among process steps, operation parameters and equipment information is accurately modeled. According to the method, firstly, a CASREL model is adopted for entity relation joint extraction, the defects of a traditional method in processing triple overlapping are overcome, and the data extraction accuracy is improved; thirdly, time information is embedded into the extracted triple, and a tetrad (entity, relation, entity and time) is generated so as to enhance the time sequence reasoning capability; time sequence reasoning is carried out through a TTransE model, and the time change rule in the technological process is accurately captured. The method breaks through the limitation of lack of time dimension in traditional data analysis, effectively improves the optimization and intelligence level of the traditional Chinese medicine preparation process, is applied to the fields of process adjustment, production scheduling, quality control and the like, can provide more accurate decision support, and pushes the traditional Chinese medicine preparation industry to develop towards the intelligent and refined direction.

This invention provides a method and system for updating a knowledge network, acquiring a multi-source collection of scientific research knowledge on pediatric oncology, encompassing structured and unstructured knowledge from multiple disciplines. It utilizes a large-scale scientific research model to align and integrate interdisciplinary knowledge, generating a pediatric oncology research knowledge network. Based on explicit associations, it generates queries and hypothesis-guided directions, constructs a multi-step interdisciplinary reasoning chain to uncover intrinsic connections, predicts potential biological mechanisms or treatment strategy optimization directions in pediatric oncology research, and supplements the knowledge network to complete dynamic updates. This invention achieves the organic integration and dynamic updating of pediatric oncology knowledge, ensuring the knowledge network remains synchronized with the latest research findings, thus improving research efficiency and promoting continuous progress in pediatric oncology research.

The invention relates to a method for deploying and optimizing a net load prediction model on a smart energy unit, and the method comprises the steps: carrying out the compatible adaption of the smart energy unit and a model, the method specifically comprises the following steps: according to the complexity, data volume and performance requirements of a model and budget research model deployment software and hardware requirements, evaluating required example support, memory and storage space requirements by analyzing the complexity of the model, and according to the model and a framework, determining whether additional dependence files are needed and researching security requirements; carrying out target detection by adopting an ensemble learning algorithm; and a time sequence event model of a self-attention mechanism is introduced to carry out fault early warning and defect elimination guidance, and the potential fault occurrence probability of the key equipment is predicted. The method has the beneficial effects that 1, the suitability of the model and the smart energy unit is improved; and 2, the model performance is improved. And 3, effective model deployment and test are realized. 4, the power market operation and regulation capability can be improved.

The invention discloses a solute element segregation grain boundary strength prediction method, and relates to the technical field of grain boundary strength prediction, and the technical scheme is characterized in that grain boundaries with different structures are selected as research models; selecting a plurality of solute atoms from the periodic table of elements and evaluating the grain boundary strength at the most stable segregation site; constructing a data set for analyzing the influence of solute segregation on the grain boundary strength; and constructing a machine learning model according to a gradient enhanced regression algorithm, and performing training and evaluation to realize grain boundary strength prediction after element segregation. According to the method, the metallic aluminum serves as a research object, segregation behaviors of various solutes in the aluminum grain boundary and the influence of the solutes on the grain boundary strength are analyzed, meanwhile, segregation and strengthening effects are comprehensively considered, solute elements with strengthening potential are screened out, and valuable theoretical guidance is provided for designing a new generation of high-strength aluminum alloy.

The invention relates to the technical field of charging facilities, and discloses a cloud-side cooperative control method, system and device for charging facilities and a medium, and the method can effectively solve the problems of uneven resource distribution, low control efficiency and the like of the charging facilities in the cloud-side cooperative control process. A charging facility cloud edge cooperative control research model is constructed, accurate modeling is performed on a charging process by using an objective function and constraint conditions, and a solid theoretical basis is provided for subsequent optimization control. According to the method, a Markov decision process framework is established, and a first improved algorithm including a dynamic normalization strategy and deterministic training is adopted for optimization, so that an optimal control strategy framework model can be quickly and accurately found, and the scientificity and effectiveness of a control strategy are improved.