54 results about "Molecular composition" patented technology

An embodiment represents composition of molecules in a feedstock as a combination of individual molecule representations and molecular attribute representations. A representation of chemistry of a chemical reaction of the feedstock in a chemical reactor is then formulated based on the representations. Then, a simulation of the chemical reaction of the feedstock in the reactor is performed using the representations to determine composition of products of the reaction. A first subset of the products are represented as individual molecule represented products, and a second subset of the products are represented as attribute represented products. In turn, the attribute represented products of the second subset are sampled to determine individual molecule representations of the attribute represented products. As a consequence of the sampling, individual molecule representations of the first and second subsets of the products of the chemical reaction of the feedstock in the chemical reactor result.

The invention relates to the field of oil reservoir exploration and development, and discloses a heavy oil micromechanism characterization method and device, a storage medium and a processor, and the method comprises the following steps: determining the molecular composition of a heavy oil sample and the content of each molecule; classifying the molecules based on the features of the molecules to obtain a classification result, and selecting at least one target molecule from each category of the classification result; establishing a heavy oil system molecular model based on a heavy oil simulation system composed of the target molecules; based on the thickened oil system molecular model and a pre-established mineral pore molecular model, establishing a thickened oil system flow model; and determining the thickened oil micromechanism according to the simulation result of the thickened oil system flow model. Based on the scheme of the application, the similarity degree of properties between the thick oil simulation system and the real thick oil system can be improved, so that the accuracy of the subsequent micro simulation result of the thick oil can be improved, and the accuracy of the obtained thick oil micro mechanism can be improved.

The present application relates to a kind of hydrolysis targeting chimera based on artificial antibody and its preparation method and application.The hydrolysis targeting chimera is composed of artificial gold antibody and molecule that can activate cell degradation mechanism, the artificial gold antibody is composed of gold nanoparticle and polypeptide coupled on the surface of gold nanoparticle, the molecule that can activate cell degradation mechanism is coupled on the surface of gold nanoparticle.The hydrolysis targeting chimera can simultaneously bind target protein and activate cell degradation mechanism, with the performance of strong specific recognition target protein, and high stability, orientation controllable.At the same time, the hydrolysis targeting chimera can also play the molecule of activation cell degradation mechanism, such as lysosome sorting signal motif, coupled on the surface, induce clathrin-mediated endocytosis, transport the complex of target protein and chimera to lysosome and degrade.The hydrolysis targeting chimera can play multi-mode cancer treatment effect by synergistic inhibition of tumor cell proliferation, invasion pathway and apoptosis activation.

The present invention provides a Zn-MOF material for high-sensitivity and high-selectivity detection of ATP / ADP, and a preparation method therefor and a use thereof. The Zn-MOF material uses zinc as a metal center and H2PDBA as a ligand. The chemical molecular formula of the Zn-MOF material is [C34H30N2O4Zn]n, wherein n represents an infinite alternating arrangement of the simplest molecular formula in the internal molecular composition of the material. The present invention further provides a preparation method for the Zn-MOF material. The preparation method comprises adding H2PDBA and an inorganic zinc compound to a first organic mixed solution and placing the mixture in a reaction kettle for a reaction to obtain the Zn-MOF material. The Zn-MOF material of the present invention can realize high-selectivity detection of ATP / ADP in water. In addition, a new fluorescent material is provided for the detection of ATP / ADP, and new ideas are provided for rationally constructing more stable MOFs in terms of structural design.

The application provides a method and system for identifying molecular composition and predicting physical properties based on a graph, and belongs to the technical field of material analysis and testing. The method comprises: performing infrared spectrum detection and gas chromatography detection on the gasoline to be detected respectively to obtain infrared spectrum data and gas chromatography data; obtaining a first predicted molecular composition according to the infrared spectrum data; identifying a second predicted molecular composition based on the gas chromatography data; performing linear addition on the first predicted molecular composition and the second predicted molecular composition to obtain an overall predicted molecular composition; and taking the overall predicted molecular composition and predicted molecular attribute information as the molecular detection result of the gasoline to be detected. The application solves the technical problems of low accuracy of gasoline molecular composition identification, great limitation of a single detection method and inaccurate physical property prediction in the prior art, achieves the technical effect of improving the accuracy of molecular composition identification through double spectrum data fusion, and realizes reliable physical property prediction based on accurate molecular composition.

The invention discloses a Q-TOF mass spectrum database system and a Q-TOF mass spectrum database method for analyzing unknown substances of medical equipment. According to the system and the method, the traditional positive matching logic of quasi-molecule ion priority is abandoned, and a reverse analysis strategy from a structural unit to a molecular structure is creatively adopted. The core of the method is that: a candidate structural unit is locked preferentially through characteristic fragment ions in a secondary mass spectrum and mass difference matching between the ions; and carrying out intelligent combination calculation by combining information of primary excimer ions (essentially adduct ions), and finally deducing the molecular composition of an unknown compound. The method effectively solves the problems that a traditional method is low in unknown derivative identification success rate and excessively depends on expert experience, minute-level efficient identification is achieved, and the efficiency, accuracy and coverage range of medical instrument leached matter identification are remarkably improved.

The present disclosure relates to systems and methods for real-time analysis and classification of tangible products based on predefined quality parameters using artificial intelligence (AI). It incorporates one or more sensors to monitor various product properties such as molecular composition, moisture content, and structural integrity. Sensor data is processed by a server, which identifies relevant characteristics like spectral peaks and dielectric constants, then generates a comprehensive aggregate signature using feature-level fusion techniques. An Al model, trained on tangible datasets, analyzes the fused data to detect deviations in quality, such as foreign particles, improper moisture, or structural defects. The system provides real-time feedback for corrective action, allowing adjustments in production parameters or sorting of defective products. In some embodiments, a handheld version of the system enables manufacturers to perform in process checks and immediately address quality issues during production.

A separation membrane for separating hydrogen and a gas L, in which an activation energy Ep(S) (kJ / mol) of a permeance P(S) (mol / (m2·s·Pa)) of hydrogen through the separation membrane derived within a range of a temperature Tam (° C.) satisfying Formula (1-I) described below and an activation energy Ep(L) (kJ / mol) of a permeance P(L) (mol / (m2·s·Pa)) of a gas L (provided that hydrogen is excluded) through the separation membrane derived within the same temperature range satisfy Formula (1-II) described below: 5 (° C.)≤Tam (° C.)≤200 (° C.) (1-I)|Ep(L)|<|Ep(S)| (1-II). There can be provided a separation membrane for separating and recovering hydrogen, a separation membrane laminated body, a separation module or separation tower, a hydrogen recovery system, and a method for separating and recovering hydrogen, which enable safe and highly efficient separation and recovery of hydrogen from a mixed gas composed of molecules having relatively close dynamic molecular diameters even when a supply pressure is relatively low, including separation and recovery of hydrogen from a hydrogen-oxygen mixed gas.

The invention relates to the technical field of veterinary drugs, and particularly provides a polynucleotide molecule composition for preventing cat infectious peritonitis, a chimeric polynucleotide molecule and an mRNA vaccine. In order to overcome the ADE effect caused by S protein full-length antigen in the prior art, FIPV N protein without ADE risk is adopted and is combined with screened S protein specific T cell and B cell epitopes. Core schemes include two classes: one is a separate polynucleotide composition comprising epitope peptides encoding N and S proteins; and 2, a single chimeric polynucleotide encoding N protein and S protein epitope peptides. The polynucleotides are optimized by codons and encapsulated in lipid nanoparticles (LNP) to prepare vaccines. Experiments prove that the vaccine can synergistically stimulate powerful immune response, the survival rate of immune cats is remarkably increased to 80%-100% from standard 40% on the premise that ADE is not caused, and FIP is effectively prevented.

The application discloses a generation method and a prediction method and device of an oil product molecular composition prediction network. The generation method comprises the following steps: obtaining an original data set; training a pre-constructed generator based on the original data set to obtain first network parameters of the generator; inputting macroscopic physical property data of a randomly generated to-be-tested oil product into the generator to obtain molecular composition data of the to-be-tested oil product generated by the generator; keeping the first network parameters of the generator unchanged, training a pre-constructed discriminator connected with the generator based on the molecular composition data of the known oil product in the original data set and the molecular composition data of the to-be-tested oil product generated by the generator to obtain second network parameters of the discriminator; keeping the second network parameters of the discriminator unchanged, and jointly training the trained generator and the discriminator based on the original data set to obtain an oil product molecular composition prediction network. The prediction network can predict the full molecular composition of the oil product.

The present application belongs to the technical field of biomass charcoal material and environmental functional material, and particularly relates to a preparation method for regulating the release characteristics and environmental stability of biochar dissolved organic matter and application thereof. The method uses cotton stalk cortex biomass as raw material, prepares biochar through limited oxygen pyrolysis, and combines particle size crushing classification and repeated crushing treatment to regulate the exposure degree of the cavity structure and skeleton structure of the biochar, so as to realize the regulation of the release amount, molecular composition, aromaticity, photochemical property and oxidation stability of the biochar dissolved organic matter. The method is simple in process, wide in raw material source, can distinguish biochar dissolved organic matter from different structure sources, and provides technical support for the application of biochar in environmental remediation, pollutant migration regulation, carbon stability evaluation and safe application.

The invention provides a pellicle drug-loading system and a preparation method and application thereof, the pellicle drug-loading system is of a structure that an outer membrane wraps a core, and the outer membrane is a bacterial outer membrane; the core is formed by loading near-infrared two-region AIE photo-thermal molecules on a tetrahedral DNA (deoxyribonucleic acid) nano structure. The invention has the advantages that: the mycoderm drug delivery system can realize spatial dual targeting and time visual regulation and control on pathogens, and constructs a positive feedback cycle of drug delivery-immune activation through triple function synergy, thereby providing a drug basis for treatment of bacterial infection.

The invention relates to a quantitative source tracing method and device for a water pollution source, and the method comprises the steps: detecting the concentrations of soluble organic carbon of samples of a target water body section, a main pollution source and a non-main pollution source, and detecting the molecular composition and molecular strength of soluble organic matters in the samples through a non-target ultrahigh-resolution mass spectrum; main pollution source representative pollution molecules which belong to the target water body cross section, are main pollution sources and do not belong to non-main pollution sources are screened out; generating a fitting curve of the representative pollution molecules of the main pollution source according to the intensity of the representative pollution molecules of the main pollution source and the concentration of the soluble organic carbon; calculating the contribution rate of the main pollution source to the dissolved organic matters of the water body, and quantitatively tracing the pollution source of the water body according to the contribution rate of the dissolved organic matters. According to the method, DOM is taken as a gripper, DOM molecular composition and molecular strength characteristics of a pollution source are obtained, and quantitative tracing of pollution is realized by screening representative pollution molecules and calculating contribution of the pollution source to water pollution.

A method implemented in a wastewater monitoring system for evaluating bioavailability of organic nitrogen in wastewater, including: obtaining, by using a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer, molecular composition information of organic nitrogen in a wastewater sample collected from a wastewater treatment plant; obtaining bioavailability data corresponding to the wastewater sample, where the bioavailability data is measured through algal bio-culture; training, by a processor of the wastewater monitoring system, a random forest model using the molecular composition information and the bioavailability data; receiving, from the spectrometer, molecular composition information of organic nitrogen in wastewater from a target wastewater treatment plant; and executing, by the processor, the trained machine learning model on the received molecular composition information to generate a predicted bioavailability value; and transmitting, by the wastewater monitoring system, the predicted bioavailability value to a process control unit of the wastewater treatment plant for real-time monitoring or process adjustment.

The invention relates to the technical field of environmental geochemistry, in particular to a degradation prediction method for soluble organic molecules based on a time sequence chart neural network. According to the degradation prediction method for the soluble organic molecules, a data set is formed based on existing water body degradation whole-process molecules, and data standardization processing is carried out according to a specified standard; converting the standard data matrix into a molecular graph network, inputting the molecular graph network into a time sequence graph neural network, and organizing the molecular graph network according to a time sequence to form a graph sequence; a dynamic graph neural network model is constructed through combination of graph network characteristics of a molecular structure and time sequence constraints of environmental conditions to realize high-precision prediction of degradation paths, rates and potential products of organic molecules in the environment under different conditions. According to the method, a rule rationality constraint and interpretability mechanism is introduced, the chemical effectiveness of a prediction result can be effectively guaranteed, an interpretability output result can be provided, and thus the reliability and interpretability of the model are further enhanced.

The application provides a biosynthetic pathway prediction method and system based on deep learning, comprising: obtaining reaction group data; constructing a fingerprint library from the reaction group data; inputting a SMILES sequence of product molecular data into a Transformer model for training; inputting a product molecule to be predicted into the trained Transformer model for precursor molecule prediction to obtain a predicted precursor molecule; forming a complete reaction from the product molecule to be predicted and any predicted precursor molecule and generating a corresponding predicted reaction fingerprint; matching and comparing the predicted reaction fingerprint with the fingerprint library; adding the predicted precursor molecule and enzyme protein corresponding to the reaction with the highest similarity to a synthesis route; determining whether the predicted precursor molecule output by the current Transformer model is a preset building block or whether a preset iteration number is reached; if yes, outputting the current synthesis route; otherwise, inputting the current predicted precursor molecule as a product molecule to be predicted into the Transformer model for precursor molecule prediction.

The application relates to a method and system for predicting the molecular level composition of a petrochemical production stream based on multiple models, and relates to the technical field of oil refining and chemical molecular management, and comprises the following steps: determining the molecular composition of raw materials, splicing structural units based on a structural unit-bonding moment matrix framework, and constructing a molecular digital structure topology; combining a preset molecular database, a probability density function and a molecular property predictor to construct a molecular composition model; establishing a molecular level reaction network based on a catalytic reforming reaction mechanism, combining a reaction rate expression to construct a molecular level reaction kinetics model; constructing a reactor model according to mass, energy and momentum transfer equations; constructing inactivation and separation unit models, coupling multiple models in sequence, generating a full-process reaction-separation molecular level prediction model, and predicting the molecular level composition of any stream. The application solves the problems that traditional petrochemical production relies on measured results to adjust process parameters and has operation lag, and through prediction of the molecular composition of a stream, the lag can be eliminated, and the production control precision is improved.

The preparation method comprises the following steps: extracting an intershell fluid active substance, extracting extracellular small vesicles as an active substance target, using hyriopsis cumingii pallium for conventional pearl mussel breeding, and preparing the bioactive preparation for skin injury repair from the raw material, so as to obtain the bioactive preparation for skin injury repair. The method comprises the following steps: collecting liquid in a gap between a pearl culture clam shell and an outer mantle, separating and extracting vesicles from the liquid through ultracentrifugation, taking freshwater pearl shell culture by-products as a sustainable source of bioactive substances, grinding the bioactive substances contained in the freshwater pearl shell culture by-products, optimizing components through molecular composition, and preparing the freshwater pearl shell culture by-products. A preparation with a stable bioactive substance structure for repairing skin injury radiated by ultraviolet rays is obtained. The extracellular small vesicles are extracted from pearl shells, the main components of the preparation are biological sources, the safety is high, the absorbability of a nanoscale molecular structure is good, an innovative solution is provided for skin repair, and high value-added conversion of pearl shells is achieved.

The present application relates to the technical field of environmental geochemistry, and particularly relates to a dissolved organic molecule degradation prediction method based on a time sequence graph neural network. The dissolved organic molecule degradation prediction method provided by the present application is based on an existing water body degradation whole-process molecular composition dataset, and data standardization processing is performed according to a specified standard. Then, the standard data matrix is converted into a molecular graph network and input into a time sequence graph neural network to form a graph sequence in time sequence organization. Through the combination of the graph network features of the molecular structure and the time sequence constraints of the environmental conditions, a dynamic graph neural network model is constructed to realize high-precision prediction of the degradation path, rate and potential product of the organic molecules in the environment under different conditions. The present application introduces a rule rationality constraint and an explainability mechanism, which can effectively guarantee the chemical effectiveness of the prediction results and provide explainable output results, thereby further enhancing the reliability and explainability of the model.

The invention relates to the field of oil reservoir exploration and development, and discloses a method and a device for characterizing a fluid mechanism in kerogen nanopores, and the method comprises the following steps: determining kerogen molecular composition in a shale sample; establishing a plurality of kerogen molecular models based on the kerogen molecular composition and the surface density test result of the shale sample; establishing a plurality of initial kerogen nano-pore models based on the plurality of kerogen molecular models, screening out a target kerogen nano-pore model from the initial kerogen nano-pore models, and performing fitting correction on the target kerogen nano-pore model based on a real pore diameter detection result; and based on the fitted and corrected target kerogen nanopore model and a pre-established fluid molecular model, establishing a model of distributing the fluid in the kerogen nanopores. The kerogen nanopore model is subjected to fitting correction based on a real pore diameter detection result, so that the similarity between the kerogen nanopore model and a real kerogen structure can be improved, and a more accurate kerogen nanopore fluid mechanism can be obtained.

The present invention relates to a method for analyzing a biological sample obtained from a subject, comprising analyzing components contained in a biological sample by an assay using a first molecule selected from the group consisting of a molecule binding to a sugar chain bindable with BC2LCN, a molecule binding to SerpinA3, and a molecule binding to Gal3BP, and a second molecule that is BC2LCN.

The present disclosure relates to a distillate molecular composition calculation method, device, equipment and storage medium, the method comprising: obtaining molecular composition data of feed of a fractionating device, and distillation range data and yield data of each product distillate, constructing a distillate cutting model based on the distillation range data and yield data, the distillate cutting model comprising temperature intervals, and content data corresponding to each temperature interval, calculating separation coefficients of each distillate in each temperature interval by using a separation coefficient calculation formula based on the distillate cutting model, obtaining a single molecule separation coefficient model, obtaining boiling point data of each single molecule in the feed based on the molecular composition data of the feed, and obtaining the content of each single molecule in each distillate based on the boiling point data and the single molecule separation coefficient model; the single molecule separation coefficient model is obtained through the distillation range data and yield data of the distillate, and the content of the single molecule in each distillate after distillation of the feed can be determined based on the separation coefficient.

The invention discloses a polymer composition and application thereof in preparation of a medicine taking a Braf protein degradation agent as an active component. The polymer composition is prepared from the following raw materials: fucoidan, hydroxyethyl cellulose and polyvinyl alcohol, according to the high-molecular composition, fucoidan, hydroxyethyl cellulose and polyvinyl alcohol with different molecular weights are adopted, a cross-linked network structure is formed through the strong hydrogen-bond interaction among molecules, the good slow-release effect on the Braf protein degradation agent is achieved, and the stability of the Braf protein degradation agent can be effectively improved; in addition, the invention also provides a pharmaceutical composition, and the pharmaceutical composition has good inhibitory activity on SK-MEL-28 human melanoma cells, has a good degradation effect on Braf protein in the SK-MEL-28 human melanoma cells, and has a good potential treatment effect on solid tumors such as melanoma.

The application discloses a kind of knee joint targeting stem cell exosome compositions and preparation method and application thereof, it is related to biological medicine technical field.The composition includes the core-shell structure that is made of stem cell exosome and the targeting stable functional macromolecule that is coated on the surface of stem cell exosome;The targeting stable functional macromolecule is made of biocompatible polysaccharide skeleton, membrane anchoring hydrophobic group and knee joint lesion targeting ligand by covalent bond connection composition.The application is integrated in the same macromolecule carrier by integrated molecular design, and by self-assembly technology, it is " dressed " on the surface of exosome, solves the technical contradiction that stability and targeting cannot be obtained in existing stem cell exosome technology.

The invention belongs to the technical field of water ecology evaluation and water environment analysis, and discloses a dissolved organic matter chemical diversity-based water ecology integrity degradation diagnosis method, which analyzes DOM molecular fingerprints in a water body through an ultrahigh-resolution mass spectrum, realizes fine characterization of DOM molecular composition complexity and change thereof, and improves the water ecology integrity degradation diagnosis accuracy. The limitation that the traditional water ecology evaluation method is difficult to identify the molecular scale recessive degradation is broken through; by constructing a chemical diversity index and introducing an interpretable data driving model, a quantitative corresponding relation between a molecular structure parameter threshold value and water body chemical integrity degradation is established, and a degradation signal of a DOM (Document Object Model) library converted from complex stability to simple activity in a water ecosystem can be stably identified; and a molecular-scale technical support is provided for lake and river water ecological integrity degradation identification and management decision.

Disease detection and characterization using computational analysis of Raman spectra is used to detect disease-specific multi-molecular patterns “spectral fingerprint” associated with specific diseases, cellular physiologic derangements, or altered metabolism from systemic reactions to disease. Comparison of the Raman spectral fingerprint of urine from subjects with specific diseases and those not (healthy persons) provides the means to identify key disease-associated changes in urine molecular composition. Methods include applying baseline correction to spectra of a desired wavenumber range e.g., with the Goldindec algorithm, or with ISREA and StaBAL; vector or specific band normalization; and one or more of principal component analysis (PCA); discriminant analysis of principal components (DAPC); principal least squares (PLS) regression, machine learning with neural networks (NN); identification of wavenumber loadings; calculation of total canonical distance (TCD); total spectral distance (TSD), total principal component distance (TPD); ANOVA; pairwise comparisons; and performing leave-one-out or multi-fold cross-validation analysis of chemometric models (DAPC, PLS, NN) to report predictive capabilities in terms of accuracy, sensitivity (true-positives), and specificity (true-negatives), positive predictive value (PPV) and negative predictive value (NPV).

The invention relates to a neodymium complex [NdL (H2O) 2]. 3H2O, HL = 1, 3, 5-tri (carboxyl methoxy) benzene. An asymmetric structural unit of the neodymium complex is composed of an Nd < 3 + >, a completely protonated carboxylic acid ligand, water molecules with two structures and three free water molecules. A central metal ion Nd < 3 + > in the molecule, eight carboxylic acid oxygen atoms on five ligands and oxygen atoms on two water molecules are subjected to ten-coordination to form a double-cap tetragonal reverse prism structure, and chains are orderly stacked into a three-dimensional structure through ligand oxygen bridging, pi-pi interaction of ligand benzene rings and hydrogen-bond interaction. The conductive potential (-0.52 eV) of the neodymium complex is more negative than that of E (H < + > / H2), the hydrogen production rate of the neodymium complex used for photocatalytic water decomposition is 18.58 [mu] mol.g <-1 >. H <-1 >, the selectivity of catalyzing benzylamine oxidation to generate N-benzyl-1-phenylmethyleneimine under the air condition is 100%, and the yield is 26.9%.

Provided in the present disclosure are a crude oil evaluation method and apparatus, and an electronic device, a storage medium and a program product. The method comprises: acquiring molecular composition data of a crude oil sample that is sent by an analytical device, wherein the molecular composition data is used for representing content data of compounds in the crude oil sample; on the basis of the molecular composition data, determining molecular characteristic data of the crude oil sample, wherein the molecular characteristic data is used for describing the chemical properties of compound molecules included in the compounds; on the basis of the molecular characteristic data, performing property prediction on the compound molecules, so as to obtain property prediction data of the compound molecules, wherein the property prediction data is used for indicating the physical properties of the compound molecules; on the basis of the molecular characteristic data of the compound molecules and the corresponding property prediction data, determining macroscopic physical property data of the crude oil sample; and outputting an evaluation result of the crude oil sample, wherein the evaluation result comprises the molecular characteristic data and the macroscopic physical property data. The present disclosure improves the efficiency of crude oil evaluation.

The present application relates to the technical field of environmental monitoring and water resource protection, and discloses a reservoir dissolved organic matter quantitative tracing method and device, an electronic device and a medium, the method comprising: performing collaborative analysis of spectrum and mass spectrum on a water sample to be measured to obtain fluorescence component characteristics and molecular composition characteristics of dissolved organic matter in the water sample to be measured; constructing a joint fingerprint characteristic vector of the dissolved organic matter in the water sample to be measured based on the fluorescence component characteristics and the molecular composition characteristics; and sequentially matching and analyzing the joint fingerprint characteristic vector with a preset potential source fingerprint database to quantitatively calculate the contribution proportion of each known pollution source to the dissolved organic matter in the water sample to be measured, so that the present application realizes the leap from qualitative discrimination to quantitative calculation of the contribution proportion of each pollution source, and significantly improves the accuracy and systematicness of identification and analysis of complex mixed sources.