20 results about "Biological interaction" patented technology

The invention discloses an ecological risk assessment method for organic pollutants in a natural water body, and belongs to the field of ecological risk assessment of the natural water body, and the method comprises the steps: building a quantitative structure-activity relationship toxicity prediction model of species based on a machine learning and feature screening method; predicting and obtaining biotoxicity data in a to-be-predicted water body by using the quantitative structure-activity relationship model, establishing a species sensitivity distribution model of pollutants in the water body according to the biotoxicity data, and calculating predicted non-effect concentration; on the basis of database retrieval, acute toxicity experiments and an inter-species relationship prediction model, collecting, predicting and supplementing toxicity data of species in the water body, and evaluating the harmfulness of pollutants in the water body by using a risk entropy method and a comprehensive scoring method respectively. According to the method, ecological risk assessment is carried out by utilizing a machine learning method, the toxicity of the persistent organic pollutants in seawater and fresh water can be effectively assessed, and the ecological risk of the organic pollutants in the water body can be effectively assessed.

The present disclosure relates to systems, non-transitory computer-readable media, and methods that a implement a framework for active learning to discover pairwise interactions via representation learning. Indeed, in one or more implementations, the disclosed systems generate a first individual perturbation embedding from a first representation of a first cell exposed to a first perturbation and a second individual perturbation embedding, from a second representation of a second cell exposed to a second perturbation. For instance, the disclosed systems combine the first individual perturbation embedding and the second individual perturbation embedding to determine a predicted pairwise embedding. Moreover, in some instances, the disclosed systems generate a pairwise embedding from a representation of a cell exposed to both the first and second perturbation. Additionally, from comparing the predicted pairwise embedding with the pairwise embedding, the disclosed systems generate a measure of biological interaction of the first and second perturbation.

The invention discloses a puzzle solution game adaptive design method and system based on ecological balance, and the method specifically comprises the steps: receiving ecological scene data selected by a player, carrying out the evaluation processing of the capability level of the player through combining with a player capability evaluation model, and generating an evaluation result; dynamically generating hierarchical ecological problems according to an evaluation result, and synchronously activating Agent behavior tree loaders of corresponding hierarchies to form an Agent modeling system; simulating a biological interaction network through an Agent modeling system, inputting real-time operation data of the biological interaction network into an LSTM double-time-sequence prediction engine for prediction processing, and generating an ecological evolution graph; and generating a dynamic visual interface according to the ecological evolution map, and triggering a difficulty regulator when detecting that the ecological imbalance index exceeds a difficulty threshold value of the current player. Complex characteristics of an ecological system are effectively simulated, more challenging and interesting puzzle solving game experience is provided for players, and meanwhile understanding and protection awareness of the players to the ecological system can be improved.

The present application relates to the technical field of ecological environment, in particular to a water ecological system evaluation system and method based on a water habitat coupling mechanism model. The technical problem is to integrate key ecological mechanisms while maintaining high computational efficiency. The system includes: an input layer that receives measured data related to the water environment of the target water habitat; a configuration layer that selects several indicators from the geographic indicators, hydrological indicators, hydrodynamic indicators and meteorological indicators input by the input layer, and configures multiple different environmental factors; key ecological processes are integrated through selective mechanism coupling, and interspecific competition factors are configured for algae and biological interaction factors are configured for fish; the simulation layer uses a differential evolution algorithm to automatically calibrate and optimize the parameters configured by the configuration layer; obtain the spatial and temporal changes of aquatic plants, algae and fish; the output layer outputs the spatial distribution results of the three species of aquatic plants, algae and fish, and provides suggestions for scenario analysis results and environmental economic balance decision-making.

The invention discloses a benthic organism sample identification and analysis method and system based on data mining. The method comprises the following steps: firstly, acquiring standard image data of benthic organisms in different growth stages, extracting appearance features and constructing a feature database; establishing an identification model based on the database, collecting target sample and community three-dimensional structure image data by using an underwater robot, and carrying out initial identification; and if the result is not unique, mining an inter-species relationship, constructing a community relationship network in combination with a graph theory algorithm, calculating the credibility of the identification result, and performing secondary identification to obtain a final result. The method improves the identification accuracy and reliability, and is suitable for marine ecological monitoring and biodiversity research.

The invention relates to a method of producing nitrogen-enhanced vermicomposting through the incorporation of nitrogen-rich Gliricidia sepium leaves into a vermicomposting substrate. Organic waste materials including animal manure, crop residues, and food waste are blended with pre-dried and shredded Gliricidia sepium foliage in optimized proportions and decomposed by epigeic earthworms (Eisenia fetida) under mesophilic conditions (20–35 °C). The biological interaction between earthworms and microorganisms results in a finely divided, porous, humus-like vermicompost characterized by increased nitrogen, phosphorus, and potassium (NPK) levels and measurable nitrogen content.

The present invention provides a method for analyzing the stability of reef fish communities based on a symbiotic graph, comprising the steps of: S1: Analyzing the stability of reef fish communities, comprehensively considering the dependence relationship and the trophic relationship to quantify the relationship between coral reefs and fish populations; constructing a symbiotic graph and using the PMA graph kernel method for similarity calculation; S2: Identifying the priority areas for protecting reef fish communities, and using the Louvain algorithm to divide the module structure of the communities in unstable years. The method for analyzing the stability of reef fish communities based on a symbiotic graph according to the present invention addresses the problems of single and less objective calculation methods for interspecies relationships in previous studies, and proposes a model that can effectively express the biological relationships of reef fish communities; addresses the problem of low accuracy of the methods for measuring community changes in previous studies, and designs a method that can effectively measure community changes to analyze the stability of the communities; and further identifies the areas that need to be protected first according to the analysis results of community stability.

The application provides a method for evaluating ecological risk of microplastics based on population and community indexes, and belongs to the technical field of pollutant risk evaluation. The application studies the influence of microplastic concentration and particle size on the filter-feeding speed of Daphnia magna, analyzes the relationship between microplastic intake and algal morphology, and studies the influence of microplastics on the movement ability and filter-feeding of Daphnia magna after the microplastics are taken into the body, so as to evaluate the ecological risk of microplastics at a concentration far below the lethal concentration from the perspective of population and community. It is found for the first time that Daphnia magna will mistake microplastics similar in size to algal cells as food, and after the microplastics are taken into the body, the behavior characteristics of zooplankton will be affected, so that the harm of microplastics to zooplankton is comprehensively evaluated from the perspective of behavior and interspecific relationship. The application provides a new idea for evaluating ecological risk of microplastics from the perspective of population and community, and provides a basis for correctly formulating pollutant emission standards.

The present disclosure relates to a liquid handling device, methods of operating a liquid handling device, a method of performing a diagnostic test, a computer program and a system. In particular, the liquid handling device is capable of controllable bi-directional or multi-directional flow of reagents across one or more reaction zones allowing rapid, precise and controllable quenching of reactions and / or biological interactions.

The application discloses a benthic organism sample identification analysis method and system based on data mining. The method first acquires standard image data of benthic organisms at different growth stages, extracts appearance features and constructs a feature database; an identification model is established based on the database, three-dimensional structure image data of target samples and communities are collected by using underwater robots, initial identification is carried out; if the result is not unique, interspecific relationships are mined, a community relationship network is constructed by combining a graph algorithm, the reliability of the identification result is calculated, secondary identification is carried out, and the final result is obtained. The application improves the identification accuracy and reliability, and is suitable for marine ecological monitoring and biodiversity research.

The invention belongs to the technical field of biology, and particularly relates to a comprehensive evaluation method for crust development quality of active algae in different environments. The invention creatively constructs a three-dimensional index system containing photosynthetic ability, stress response and structural morphology, and provides a comprehensive evaluation method for the development quality of algae crust based on multi-dimensional environment-biological index integration. According to the method, a three-dimensional index system of photosynthetic capacity, stress response and structural morphology is constructed, and weight calculation of factor analysis-principal component analysis and a membership function quantification mechanism are combined, so that non-destructive, quantitative and comprehensive evaluation on the development level of algae crust is realized; the problems of index singleness, methodology limitation, lack of environment-biological interaction mechanism and the like in the existing biological soil crust evaluation technology are solved, a quantifiable ecological restoration evaluation tool is provided for desertification control, and the method has a wide application prospect.

The present invention relates to a method for storing protein-modified nanoparticles on a paper substrate without irreversible binding, in particular a method for storing protein-modified nanoparticles within a polymer-modified paper substrate. The present invention also relates to a reservoir containing protein-modified nanoparticles capable of establishing biological interactions obtained by this method and its use in a biosensor made of paper.

The invention relates to the technical field of abandoned mine recovery evaluation, in particular to an abandoned mine natural recovery evaluation method based on ecological element collaborative characteristics, and the method comprises the steps: obtaining data; performing primary judgment; performing secondary judgment; and finally carrying out collaborative judgment. And adjusting a threshold value and generating an evaluation report. According to the method, the vegetation coverage is rapidly and preliminarily identified; secondly, evaluating the internal recovery potential of the starting area from the dimensions of provenance, microorganism, hydrological connectivity and the like; and finally, for the potential-sufficient region, accurately judging a system which is still fragile in function and a health system which has formed stable self-maintenance capability by quantifying water and soil vegetation process coupling, a biological interaction network and anti-interference capability, and dynamically adjusting an initial threshold value based on the time sequence stability of a classification result of each region. The whole evaluation system has a data-driven adaptive capability, and the problems of low evaluation result accuracy and response speed lag caused by single evaluation dimension are effectively solved.

The present disclosure relates to systems, non-transitory computer-readable media, and methods that a implement a framework for active learning to discover pairwise interactions via representation learning. Indeed, in one or more implementations, the disclosed systems generate a first individual perturbation embedding from a first representation of a first cell exposed to a first perturbation and a second individual perturbation embedding, from a second representation of a second cell exposed to a second perturbation. For instance, the disclosed systems combine the first individual perturbation embedding and the second individual perturbation embedding to determine a predicted pairwise embedding. Moreover, in some instances, the disclosed systems generate a pairwise embedding from a representation of a cell exposed to both the first and second perturbation. Additionally, from comparing the predicted pairwise embedding with the pairwise embedding, the disclosed systems generate a measure of biological interaction of the first and second perturbation.

The present application belongs to the technical field of ecological environment protection, and particularly relates to a quantitative reconstruction method of interspecific relationship of biological community, comprising the following steps: S1, lake biological-environment database arrangement; collecting and arranging the lake biological-environment database of the region, establishing the regional biological database of all specific biological groups appearing in the surface sample of the lake, and standardizing the data of the water environment physicochemical indexes corresponding to each lake after summarizing to form the regional environment database; S2, collection of lake drilling data; using a Kajak gravity sampler to extract the sediment drilling at the central position of the lake and to divide the sample, the sample is placed in a self-sealing bag, transported in cold storage, and stored in a room at -20 DEG C for physicochemical index analysis and biological species identification. The niche breadth and overlap of the internal species of the biological community are calculated, the coexistence relationship between the species in the lake is quantified, and a dynamic evaluation tool of the interspecific relationship is provided.

An improved biofilter design and related methods of utilizing shaped drain assemblies for directing fluid flow though a biofilter media to promote biological interaction. A shaped drain assembly can include a plurality of elongated drain structures having a permeable upper surface, a. lower surface and a drain interior defining a drain cross-section. When configured as a shaped underdrain assembly, each elongated drain structures can be in proximity to a biofilter tank floor such that the lower surface is in fluid communication with one or more flow channels below the floor and with the permeable upper surface supporting the biofilter media. The biofilter can include a shaped drain assembly positioned above the shaped underdrain assembly and located within or above the biofilter media. The shaped drain assemblies can control the flow and mixing of two or more flow species into the biofilter media.

The application discloses a method for improving coal mine acidic soil in northern grassland area, which comprises the following steps: firstly, dividing the original soil into two layers, i.e., a reduction neutral surface soil layer and a reduction barrier layer; secondly, excavating the original soil from top to bottom to form an excavation area, mixing the excavated soil with an acidic improver to form improved surface soil; thirdly, laying the reduction barrier layer at the bottom of the excavation area, which is made of reduction material and clay particles; and finally, backfilling the improved surface soil to generate acid-base conditions suitable for the growth of acid-resistant plants. The method can effectively reduce the acidity of the coal mine soil in the northern grassland area through the physical-chemical-biological interaction mechanism.

The present disclosure relates to systems, non-transitory computer-readable media, and methods that a implement a framework for active learning to discover pairwise interactions via representation learning. Indeed, in one or more implementations, the disclosed systems generate a first individual perturbation embedding from a first representation of a first cell exposed to a first perturbation and a second individual perturbation embedding, from a second representation of a second cell exposed to a second perturbation. For instance, the disclosed systems combine the first individual perturbation embedding and the second individual perturbation embedding to determine a predicted pairwise embedding. Moreover, in some instances, the disclosed systems generate a pairwise embedding from a representation of a cell exposed to both the first and second perturbation. Additionally, from comparing the predicted pairwise embedding with the pairwise embedding, the disclosed systems generate a measure of biological interaction of the first and second perturbation.

This invention relates to a machine learning-based method and system for predicting interspecific toxicity. The method acquires toxicity data of the same chemical to both alternative and predicted species, calculates its molecular descriptors, and preprocesses them to select descriptors suitable for modeling. Combining the toxicity data of the alternative species with the selected descriptors as independent variables and the toxicity data of the predicted species as the dependent variable, a machine learning algorithm is used to construct an interspecific toxicity relationship prediction model. The model's performance is then evaluated and validated through cross-validation. For a chemical to be predicted, only its toxicity data to an alternative species and related molecular descriptors need to be acquired. The validated final interspecific relationship prediction model is then used to predict the toxicity of the chemical to the predicted species. Compared to existing technologies, this invention utilizes a reliable model to efficiently and accurately predict the potential toxicity of a chemical to a target predicted species, effectively reducing the cost and time of traditional cross-species toxicity testing.

The invention discloses a mine restoration effect prediction method and system based on soil data analysis, and relates to the field of mine ecological restoration, and the method comprises the steps: S1, deploying a bionic sensor network with a self-adaptive triggering capability in a restoration region, obtaining soil multi-modal data before, during and after restoration, and synchronously obtaining background data of a reference ecological region; and the bionic sensor network adaptively switches a monitoring mode and a sampling frequency according to the soil temperature and humidity, a biological disturbance signal or a preset repair event. According to the method, the bionic adaptive sensor network is introduced to actively capture soil-biological interaction key signals, a seed bank-soil-microorganism collaborative response model is constructed to reveal an ecological restoration internal mechanism, and the problems that in the prior art, data and the ecological process are disjointed, the model generalization ability is weak, and prediction lags are effectively solved.