14results about How to "Help identify" patented technology

The invention discloses a molecular property prediction large language model construction method based on a knowledge graph. The method comprises a plurality of steps: firstly, acquiring pre-training corpora by using a high-throughput data acquisition technology, including related data such as molecular attributes and metabolic pathways; then, a knowledge graph about fourteen end points is constructed based on the data, and the knowledge graph represents the relation between the molecules and the attributes and the end points of the molecules in a triple form; thirdly, pre-training the large language model by using a LoRA technology, optimizing the model by adopting an incremental learning strategy, and forming an expert large model; then, a triple related to the target endpoint is retrieved from the knowledge graph through the RAG technology, and retrieval results are sorted; and filtering the retrieved triple through cue word design and an expert large model, and extracting key information. And finally, converting the filtered triple list into a natural language, inputting the natural language into an expert large model, generating a prediction result of molecular properties, and providing a reasoning basis. According to the method, the accuracy and efficiency of molecule and endpoint chemical reaction prediction are remarkably improved.

The invention provides a folate receptor targeting small molecule compound, a preparation method, a composition and application. Specifically provided is a compound represented by formula I or a pharmaceutically acceptable salt thereof. The compound or the pharmaceutically acceptable salt thereof provided by the invention can be used as a small-molecule targeting fluorescence contrast agent for assisting surgical treatment, has the advantages of novel structure, good solubility, small steric hindrance and strong targeting property, can obviously improve the view field of tumor surgery, and is beneficial to efficiently and accurately implementing excision of pathological tissues such as tumor tissues, boundary tissues and the like. # imgabs0 #

The invention provides a method and system for evaluating the influence of setting off fireworks and crackers on PM2.5 concentration, and relates to the technical field of environmental atmospheric pollutant evaluation, and the method comprises the steps: obtaining evaluation data of each time point in a setting off period of a monitoring station, including metal ion concentration, meteorological conditions and spatial-temporal characteristics; based on the evaluation data, the PM2.5 concentration under the firework setting-off scene and the PM2.5 concentration under the firework-free setting-off scene are predicted through a firework scene model and a background reference model; and calculating the contribution rate of the set-off fireworks and crackers to the PM2.5 concentration from two aspects of a single time point and a whole set-off time period by utilizing the predicted value of the PM2.5 concentration. According to the method, based on the firework scene model and the background reference model, efficient and accurate quantitative analysis on the influence of the set-off fireworks and crackers on the PM2.5 concentration is carried out from the two aspects of the single time point and the whole set-off time period.

The present invention discloses a method for improving the resolution of a traffic space-time map. The method comprises: collecting data and drawing an original traffic space-time map; dividing the space-time map into grids, projecting the collected data according to the grids, and calculating the average speed of each grid; further refining the grids and constructing a fine-grained grid speed prediction model; using the fine-grained grid speed prediction model to perform predictions and generate a high-resolution traffic space-time map. It can be seen that the present application divides the original "rough" traffic space-time map into grids, completes the sub-grid speed prediction using a fine-grained grid speed prediction model, and reproduces the "beautified" refined traffic space-time map, thereby achieving the function of improving the resolution of the traffic space-time map. In this way, more accurate basic analysis data for traffic status analysis and traffic event identification can be provided to traffic managers, supporting the formulation of traffic decisions.

The application provides a base sequencing quality evaluation method and system, which are used in the field of gene sequencing. The base sequencing quality evaluation method provided by the application comprises the following steps: providing a standard nucleic acid sequence, aligning the standard nucleic acid sequence to a reference sequence, and giving a label to a base in the standard nucleic acid sequence according to an alignment result; training a classifier to fit a relationship between a sequencing signal feature of the base and the label; providing a to-be-tested nucleic acid sequence, taking the base as a basic unit, and calculating the sequencing signal feature of the base in the to-be-tested nucleic acid sequence; and giving at least two quality values to the base in the to-be-tested nucleic acid sequence.

The application discloses a kind of based on digital steel coil's full life cycle product carbon footprint calculation method, comprising the following steps: A1: determining the system boundary of carbon footprint in the full life cycle of digital steel coil, and collecting activity data;A2: according to the actual production process and material consumption data of digital steel coil, determine the direct carbon emission source and indirect carbon emission source of each stage;A3: determine and collect the direct carbon emission source factor and indirect carbon emission emission factor in each stage;A4: using the emission factor of direct carbon emission source and the emission factor of indirect carbon emission source, build the carbon emission calculation model of each stage, obtain the partial carbon emission of each stage, and corresponding carbon load type;A5: using the production process path of digital steel coil, the carbon emission of last stage product is transferred to the material input of next stage, and the cumulative carbon emission of each stage product is obtained.The life cycle carbon footprint of digital steel coil is obtained by the carbon emission calculation model of each stage.

The invention belongs to the technical field of Internet of Things communication, and particularly discloses an optimized clustering routing design method applied to a WSN (Wireless Sensor Network), which adopts the specific technical scheme that an improved spectral clustering method is utilized to perform clustering operation on a WSN node structure, a transmission path of WSN nodes is preliminarily planned, a shortest path from each point to a cluster head is constructed, and a clustering result is obtained; according to the two improved methods, factors such as node residual energy, distance, load, relay node selection times and the like are comprehensively considered, a final value is solved by combining a weight value of a CRITIC design edge to replace an own edge weight value of a Dijkstra and an undirected graph in spectral clustering, and finally, respective energy consumption values of each Dijkstra algorithm transmission path and a point-to-point transmission path are compared to obtain a final value. According to the method, the energy consumption during data transmission is reduced, the life cycle of the nodes is prolonged, the death rate is reduced, and the energy balance of the WSN is enhanced.

The invention discloses a digital human interaction strategy optimization method based on big data recognition, and relates to the technical field of intelligent interaction and digital human, and the method comprises the steps: collecting and storing multi-modal interaction data, such as texts, voices, expressions and time lengths, generated in a digital human interaction process of a user; performing emotional state labeling on the multi-modal interaction data based on a pre-trained emotion recognition model, and extracting an emotional feature vector containing emotional polarity, emotional intensity and emotional stability; constructing a user emotion change track map to recognize an emotion state conversion mode; evaluating and sorting candidate interaction strategies according to the conversion mode in combination with historical interaction data, and selecting an optimized interaction strategy; and the strategy evaluation index is updated according to user feedback, so that the adaptive optimization of the digital human interaction strategy is realized.

The invention provides a primer composition for detecting hereditary thrombophilia related gene mutation and application of the primer composition, and relates to the technical field of gene detection. The primer composition comprises a PCR (Polymerase Chain Reaction) amplification primer and an extension primer, wherein the PCR amplification primer is used for carrying out specific amplification on 24 single nucleotide polymorphic sites of 22 genes, and the extension primer is used for carrying out single base extension on the 24 single nucleotide polymorphic sites. According to the primer composition, by selecting twenty-four specific loci of twenty-two genes covering key systems such as coagulation, anticoagulation and the like, a detection system which is adaptive to genetic characteristics of specific people and takes pathopoiesis and risk factors into account is constructed, so that the limitation of race heterogeneity of conventional indexes is effectively overcome; and major mutation and a multi-gene minor accumulation effect can be captured at the same time, so that individual genetic susceptibility is comprehensively analyzed, and a systematic and accurate basis is provided for accurate screening and diagnosis and treatment of hereditary thrombophilia.

The application discloses a laser radar point cloud data pseudo-image coding method for three-dimensional target detection, solves the problems of complex coding process, high information loss and low coding efficiency in the prior art, realizes efficient coding of laser radar point cloud data, and has high precision and real-time performance in target detection, and the method comprises the following steps: acquiring laser radar point cloud data, calculating the grid space coordinates corresponding to each point of the laser radar point cloud data and the reflection intensity corresponding to the grid space coordinates according to the detection range and the grid space division resolution parameter of the laser radar point cloud data; coding the grid space coordinates corresponding to each point of the laser radar point cloud data to obtain position distribution information of a height perception space as a first pseudo-image; coding the reflection intensity to obtain maximum intensity distribution information as a second pseudo-image; and splicing the first pseudo-image and the second pseudo-image to obtain a coding feature pseudo-image.

The invention provides a cardiovascular blood flow limitation prediction model construction method based on hemodynamics, belongs to the technical field of cardiovascular model construction, and comprises the steps of obtaining medical image data of a to-be-tested person, synchronously collecting specific physiological parameters, reconstructing a three-dimensional geometric model and a multi-scale simulation model of a lesion blood vessel, and constructing a cardiovascular blood flow limitation prediction model. A reference model representing the blood vessel health state is generated; setting that the three-dimensional geometric model and the reference model share the same inlet boundary condition, outlet boundary condition and wall surface boundary condition; under the boundary condition, synchronous simulation calculation is conducted on the three-dimensional geometric model and the reference model through the same numerical method, and hemodynamic parameters are obtained; and respectively calculating an energy index, a functional index and a wall surface index based on the hemodynamic parameters, carrying out weighted integration on the three indexes to obtain a comprehensive score, and outputting a prediction result of blood flow limitation according to the comprehensive score.

This invention provides a deep learning-based method, system, and device for grading cervical immunohistochemical lesions, relating to the interdisciplinary field of deep learning and medicine. Through data acquisition and preprocessing, digital images of cervical immunohistochemical slides are obtained, acquiring the RGB matrix and corresponding image data. Deep learning is used to obtain corresponding data features, which are then fused using a Transformer model. A reference feature library is constructed, and error thresholds for different CIN levels are preset. The total error between the input sample and the corresponding reference feature in each sub-region is calculated to determine the lesion level of each sub-region. Evaluation is then performed to obtain the grading result for the current region to be graded. By introducing multiple modal information such as RGB image features and image spatial features, combined with a dynamic attention mechanism and a multi-scale error evaluation strategy, automated and refined grading of cervical lesions is achieved.

The invention relates to the technical field of induced polarization detection, and discloses a multi-channel induced polarization system for geological exploration, which comprises a multi-channel acquisition module and an intelligent detection module. According to the multichannel induced polarization system for geological exploration, power supply data and current data at all time points are acquired through the multichannel acquisition module and are classified to form a data set, the intelligent detection module analyzes apparent resistivity and polarizability between an electric field and current, conductivity and charge accumulation capability of an underground medium are visually reflected, and the accuracy and the reliability of the system are improved. A monitoring period with a fixed time length is set, the change trend of apparent resistivity and polarizability is analyzed, a fluctuation index and a stability coefficient are generated, the electrical fluctuation degree and stability of the underground rock stratum are quantitatively evaluated, the multi-channel parallel detection precision is high, the intelligent detection module sets a resistance threshold value, a polarization threshold value, a fluctuation threshold value and a stability threshold value in a fixed range, and the detection accuracy is high. The method is used for judging the water saturation, mineralization components and heterogeneity of underground rock strata and outputting corresponding judgment results, and intelligent evaluation and exploration efficiency is high.

A composite wetland water cycle simulation method and system based on digital twinning belong to the field of water conservancy informatization and digital twinning technology. In view of the problem of insufficient accuracy caused by ignoring the dynamic change of vegetation and lacking adaptive calibration in traditional wetland water cycle simulation, the method comprises the following steps: constructing a three-dimensional digital base of the wetland and generating an unstructured grid; deploying multispectral sensing equipment to obtain vegetation spectral characteristics, and inversing leaf area index and average vegetation height, and the collection frequency is dynamically triggered by the digital twinning model; establishing a segmented dynamic mapping of the submerged state of vegetation and the resistance of water flow, dynamically calculating the Manning roughness coefficient and the transpiration loss term; substituting into the shallow water equation set to perform water cycle simulation; comparing the simulated water level with the measured water level, and triggering adaptive calibration when the deviation shows statistical consistency, and using the sequential data assimilation algorithm to update the key weight coefficients of the mapping model online. The system corresponds to realize the above steps. The application improves the accuracy and adaptability of composite wetland water level and flow velocity simulation.