823 results about "Natural environment" patented technology

The invention relates to the technical field of port planning and construction, and particularly discloses a port planning and construction environment feasibility assessment method and system, and the method comprises the following steps: S1, obtaining planning parameters, real-time environment monitoring data, a historical ecological data set and social economic data of a target port; s2, constructing a dynamic coupling model of environmental bearing-ecological disturbance-pollution diffusion-social economic influence; and S3, based on the dynamic coupling model, adopting multi-scene space-time prediction simulation, and outputting an environmental feasibility comprehensive index, a key constraint factor and a social economic influence evaluation result. A dynamic coupling model of environment bearing, ecological disturbance, pollution diffusion and social economic influence is constructed, the four sub-models interact in real time through bidirectional data flow, full-dimension dynamic coupling evaluation of natural environment, ecological system, pollutant migration and social economic factors is achieved, and compared with traditional single-factor evaluation, the comprehensive evaluation accuracy is improved.

The invention discloses a method for efficiently screening saline-alkaline tolerant rice. According to the method, controllable indoor saline-alkali environment simulation conditions are constructed, various salts are mixed in proportion to prepare solutions with different salinity gradients, the pH value is adjusted, and temperature, humidity and illumination parameters are accurately controlled; the method comprises the following steps: disinfecting rice seeds, carrying out a germination test, transplanting rice seedlings, and regularly measuring growth indexes; in the treatment process, physiological indexes such as malondialdehyde content, antioxidant enzyme activity, proline content and the like and the expression level of salt and alkali tolerance related genes are detected, key indexes are screened by applying statistics and multivariate analysis methods, and an evaluation system is established for comprehensive score screening. The method can quickly perform saline-alkali stress treatment on a large number of rice seeds or seedlings, is not limited by natural environment, shortens the screening period, can accurately simulate different saline-alkali soil environments, scientifically evaluates the saline-alkali tolerance of rice from multiple dimensions, and provides an efficient and reliable technical means for breeding saline-alkali tolerant rice varieties.

The invention discloses a biological environment-friendly clothing material with a self-cleaning function and a preparation method of the biological environment-friendly clothing material. According to the invention, the environmental friendliness is obviously improved, and natural components which can be completely biodegraded are adopted and can be quickly decomposed in the natural environment, so that the micro-plastic pollution is reduced; the self-cleaning function is enhanced, and through the synergistic effect of the bionic hydrophobic surface and photocatalytic decomposition, automatic falling and decomposition of stains are achieved; the durability is enhanced, a dynamic self-repairing network can automatically repair daily wear, the service life is prolonged, and the bio-based raw materials are natural, skin-friendly and excellent in air permeability. The supercritical fluid processing and microwave shaping technology replaces a high-energy-consumption process; emission of toxic substances is eliminated, and organic solvents and fluorine-containing compounds are forbidden in the whole process; raw material loss is reduced, and the using amount of functional materials is reduced through an accurate structure regulation and control technology; the maintenance cost is simplified, and the washing frequency and the use of chemical cleaning agents are reduced due to the self-cleaning characteristic; waste is compressed, and resource utilization of by-products is achieved through a closed-loop production system.

The invention relates to a landslide intelligent early-warning method based on an aging damage mechanism, and the method comprises the steps: building a landslide numerical model, and carrying out the assignment of the mechanical parameters of a rock-soil body; setting a numerical calculation initial condition and a boundary condition for elastic calculation, and calculating and generating a landslide initial ground stress model; calling the dynamic constitutive model, and performing numerical calculation through a creep command; embedding an improved tangent angle threshold algorithm; the system collects monitoring data in real time and automatically completes damage accumulation quantification based on the aging damage dynamic constitutive model; embedding the aging damage early warning model identification system into a computer system; and calculating and identifying the aging damage early warning model, and outputting an early warning result. According to the invention, through the dynamic damage model, the damage evolution rule of the rock-soil body under the long-term natural environment effect is accurately reflected, and the timeliness and accuracy of the early warning system are ensured; the corrected tangent angle lower limit value is adopted, so that the reliability of landslide early warning is improved, the landslide can be found and early warned earlier, and disaster prevention and reduction of the landslide are facilitated.

The invention discloses an SCAR marker for identifying onion pollen pollution and application thereof, the specific fragment length of the SCAR marker is 811bp, the nucleotide sequence of the SCAR marker is as shown in SEQ ID NO.1, and the SCAR marker of the onion has no target band; the invention also discloses a specific primer of the SCAR marker. When the marker determined by the method is used for verifying the allium fistulosum of different varieties and the allium fistulosum YZD polluted by the onion pollen, the allium fistulosum and the allium fistulosum YZD polluted by the onion pollen can be rapidly and stably identified, compared with a traditional seed purity identification method, the method is not influenced by natural environment and human factors, batch experiments can be carried out, the identification efficiency is improved, and the method is suitable for large-scale popularization and application. The invention provides a rapid and feasible method for solving the problem that allium fistulosum varieties are mixed due to the fact that allium fistulosum pollen is polluted by onion pollen in production.

The invention belongs to the technical field of agronomy experiment devices, and particularly relates to a mulch-mulched soil environment simulation device which comprises a closed space, an air inlet and an air outlet. The mulching film sample is arranged in the closed space; the top of the soil simulation assembly is in contact with the bottom of the mulching film sample, and the soil simulation assembly is used for simulating a soil environment covered by the bottom of the mulching film sample; the natural environment simulation assembly is communicated with the closed space, the natural environment simulation assembly is used for simulating environmental conditions of the top of the mulching film sample, and the environmental conditions comprise temperature and humidity parameters, illumination parameters, rainfall parameters and wind speed parameters. According to the invention, researchers can accurately and controllably carry out experiments indoors, simulate soil states under different mulching film materials and environmental conditions, and deeply understand the influence of mulching film mulching on key parameters such as soil moisture, temperature and gas exchange. Scientific basis is provided for agricultural production and crop management, and sustainable development of agriculture is promoted.

The invention relates to the technical field of electronic component rain test, and discloses electronic product waterproof test equipment, which comprises a test box body, a cylinder and a water pipe, a turntable is arranged in the test box body, a rotating shaft is mounted on the turntable, a cavity is formed in the test box body, and a servo motor is fixedly mounted in the cavity. An electric push rod is fixedly mounted at the output end of the servo motor, and an electronic component is further arranged on the turntable; a support is fixedly installed in the test box body, a water storage frame rotationally connected with the support is installed on the support, and a wave making mechanism is further arranged in the water storage frame. According to the electronic product waterproof test equipment, through the collaborative design of a triangular arc-shaped protruding block and a wave making floating body, a soaking test is upgraded from static water level simulation to dynamic wave impact; the arc-shaped protruding blocks intermittently impact the rolling wheels, rapid resetting of the floating body is achieved through the spring mechanism, the dynamic hydraulic action of water fluctuation on electronic components in the natural environment can be reproduced, and the limitation that traditional equipment can only achieve static soaking is overcome.

The invention discloses a natural growth apple three-dimensional attitude recognition method based on a real-time multi-task fusion algorithm, and the method comprises the steps: obtaining an aligned RGB-D image through a depth camera, constructing a data set in combination with an image enhancement technology, and synchronously training a classification, segmentation and key point detection model through a multi-task deep learning framework; judging the contour form of the apple through the classification model, and carrying out contour fitting by adopting a convex hull algorithm and an arc adjacency matrix ellipse detection algorithm; two-dimensional centroid positioning and three-dimensional point cloud analysis technologies are fused, and bimodal calculation in the three-dimensional fruit axis direction is realized in combination with a fruit stem and calyx key point detection result. According to the method, the precision problem of apple posture recognition in a complex natural environment is effectively solved, the anti-interference capability is remarkably improved through the three-dimensional point cloud denoising and feature value analysis technology, and reliable technical support is provided for automatic picking and growth monitoring.

The invention relates to a petroleum polluted soil polycyclic aromatic hydrocarbon migration path simulation experiment system, which comprises a main reaction cabin, a mechanical arm collaborative operation module, a multi-mode sensing module, a whole natural environment regulation and control module and an edge intelligent decision-making platform, an annular magnetic suspension track is arranged at the top of the main reaction cabin, and a soil sample chamber is arranged at the bottom of the main reaction cabin; the multi-modal sensing module comprises an EIT (electrical impedance tomography) module, an LIBS (laser-induced breakdown spectroscopy) module and a terahertz time-domain spectroscopy module and is used for measuring global conductivity distribution of soil in a soil sample chamber, inverting the porosity of the soil sample and a pollutant concentration field in pore water, analyzing the concentration of carbon, hydrogen and oxygen elements of pollutants and specifically detecting polycyclic aromatic hydrocarbon molecules; the edge intelligent decision-making platform interacts with the multi-mode sensing module, the full-natural-environment regulation and control module and the mechanical arm collaborative operation module to actively adjust system parameters, and repair intervention is carried out on soil body degradation. And automatic preparation of the polluted soil can be realized, and migration monitoring under different practical engineering application working conditions can be realized.

The invention provides a foreign matter intelligent identification and dynamic monitoring method based on remote sensing data fusion, and belongs to the field of image identification. The problem of low foreign matter recognition efficiency is solved; the method specifically comprises the following steps: acquiring and extracting fusion features of remote sensing pictures of various road foreign matters; similarity learning is carried out on the fusion features, and a high-dimensional index structure is established; acquiring a real-time remote sensing picture on the road, and judging whether foreign matters exist on the road or not; if so, marking a foreign matter; if not, not processing; acquiring a historical natural image of a target area, designing a time sequence feature analysis module, a spatial feature analysis module and a spatio-temporal joint prediction module, and outputting a natural environment prediction image of the target area at a future moment; acquiring an actual remote sensing image, and marking an abnormal region in the actual remote sensing image according to the natural environment prediction image; according to the method, the foreign matter recognition efficiency is improved through obtaining and feature extraction of the remote sensing images in the road and natural environment of the target area.

The invention discloses a method and a system for evaluating the nonlinear influence of a greenbelt landscape pattern on a rainfall flood regulation service. The method comprises the following steps: step 1, constructing a basic database; 2, processing data variables; 3, constructing a nonlinear model: taking a green land landscape pattern factor as a core explanation variable, taking a rainfall flood regulation service index as a response variable, introducing a natural environment factor and a social economic factor as control variables, training the random forest model, and constructing a rainfall flood regulation service prediction model; 4, key factors are identified, wherein the top-ranked factors are regarded as key factors playing a role in rainfall flood adjustment service; step 5, analyzing a key threshold: performing visual analysis on a nonlinear relationship between the key factor and the rainfall flood adjustment service by adopting a partial dependency graph algorithm; and by observing positive and negative influence trends and change rates of the key factors on the rainfall flood regulation service indexes in different value intervals, identifying potential key thresholds.

The invention relates to the technical field of marine surveying and mapping, and discloses a sea level change trend accurate calculation method based on multi-source data fusion, which comprises the following steps: acquiring multi-source satellite height measurement data, performing data grouping, establishing a plurality of average sea level models, establishing a time-varying average sea level model through the average sea level models, and calculating the sea level change trend according to the time-varying average sea level model. And performing linear regression fitting on the average sea surface height time sequence at each grid point, constructing a grid average sea level change model, and calculating a change trend at each grid point. The method can improve the separation capability of signals with different time scales in sea level changes, is not affected by extreme climate events, natural environment changes and physical environment correction, and can greatly improve the prediction accuracy of the sea level trend.

The invention relates to the technical field of periphyton incubators, and discloses a device for culturing periphyton, which comprises an incubator body, a control operation panel connected to the top of the incubator body and a culture container connected in the incubator body. Through mutual cooperation of an arc-shaped box, a chain, a chain wheel and a lamp shaft seat, the visible light simulation illumination lamp with the wavelength of 400-700 nm can move and is similar to rising of the sun from low to high and then gradually reduced, so that the illumination position is dynamically changed, a more natural growth environment is simulated, the illumination intensity and the duration time are synchronously controlled, and the illumination effect is improved. Therefore, the proper growth temperature in the incubator is maintained, the change rule of the illumination intensity and the illumination angle in one day is truly represented, artificial stable growth conditions closer to the natural environment are provided for periphyton, and efficient growth and metabolism of periphyton at the proper temperature are promoted.

The invention discloses a bacteriostatic and antiviral bamboo pulp paper-based sanitary isolation bag as well as a preparation method and application thereof, and belongs to the field of functional paper-based packaging materials. The isolation bag takes bamboo pulp fiber paper as a base material, and the surface of the isolation bag is coated with a water-based polyhydroxyalkanoate functional coating. According to the preparation method, a special polyphenol derivative-chitosan quaternary ammonium salt-nano zinc oxide organic-inorganic hybrid factor is introduced, and the problem of agglomeration of nano particles is effectively solved by utilizing the special bridging effect of polyphenol, so that high-density cation capture and oxidation inactivation sites are constructed on the surface of the coating. Compared with the prior art, the method has the advantages that the method does not need to depend on organic fluorine compounds, and the excellent waterproof and oil-proof barrier effect and the efficient inactivation of viruses can be achieved only through the extremely low coating amount. In addition, the isolation bag has unique environmental chemical responsiveness, can be efficiently dissociated under the alkaline condition to facilitate repulping recovery, can be completely biodegraded in the natural environment, and perfectly considers the requirements of biological safety protection and green environmental protection.

The invention belongs to the technical field of abnormal behavior analysis, and particularly discloses a security and protection monitoring abnormal behavior recognition method based on artificial intelligence, and the method comprises the steps: firstly collecting construction videos and natural environment data, and obtaining construction environment data through a construction management system; identifying personnel and security configuration features by using a machine vision technology, and performing statistics on environmental feature indexes through data mining and performing multi-modal fusion; then building an environment influence and process interlacing influence model, and outputting corresponding influence factors; according to an output result, an abnormal evaluation triggering index is defined, and an abnormal behavior recognition model is built for judgment; and finally, matching a judgment result with an early warning triggering mechanism and performing early warning. According to the invention, the construction site can be monitored in an omnibearing and multi-dimensional manner, and influence factors in multiple aspects are integrated. Meanwhile, by means of model building and analysis, a scientific basis is provided for judgment of abnormal behaviors. And timely and effective early warning can be realized.

The invention discloses a multi-scenario land utilization carbon reserve simulation method based on combination of deep learning and a PLUS-InVEST model. The method comprises the following steps: collecting and preprocessing historical land utilization, natural environment and social economic data; analyzing land utilization change characteristics; optimizing an LEAS module of the PLUS model by using a deep neural network, excavating a nonlinear relationship between land utilization expansion and driving factors, and generating an expansion probability graph; configuring a neighborhood weight and a transfer matrix of the CARS module; predicting future land utilization requirements under different scenes by adopting a long-short-term memory neural network; inputting the demand into a CARS module, and simulating and generating a future land utilization space pattern under multiple scenes in combination with differential constraint conditions; based on the InVEST model carbon reserve module and the carbon density data, calculating, comparing and analyzing the carbon reserve of each scene; and outputting a result, carrying out precision verification, and proposing a land utilization planning and carbon regulation strategy. According to the method, the land utilization simulation precision and the carbon reserve evaluation scientificity are improved, and decision support is provided for regional low-carbon land utilization.

The invention relates to the technical field of computer vision, in particular to an improved YOLOv8n-based unmanned aerial vehicle litchi image detection method, which comprises the following steps of: acquiring a litchi image data set of a litchi orchard; a YOLOv8-litchi model based on the YOLOv8n model is constructed; training set data are input into the model for training, and detection and classification of the litchi fruits are completed; and inputting test set data into the model to realize accurate detection of the litchi fruits. According to the invention, an RCS-OSA module is introduced to improve a YOLOv8 network model, the feature extraction capability of a feature acquisition module is enhanced, the calculation complexity is reduced, effective information of the module is successfully fused by introducing a BiFPN network structure, the detection capability of a detection model is enhanced by using a DynamicHead detection head, and the detection efficiency is improved. And finally, the detection precision, the generalization ability and the robustness of the model are enhanced, so that relatively high accuracy is obtained in a natural environment.

The invention discloses a method and system for automatically segmenting and extracting hyperspectral information of oil tea fruits in situ, and the method comprises the steps: obtaining an RGB image and a hyperspectral image of the oil tea fruits in a natural environment, and constructing a source domain and target domain data set; performing pre-training on the CA-TransUNet + + model by using the source domain, and then introducing a target domain based on a pre-training weight to perform fine tuning so as to obtain a final camellia oleifera fruit semantic segmentation model; and then, performing refined segmentation on a fruit adhesion region in the segmented image through a spectral clustering algorithm, and combining a result with an original hyperspectral image to realize automatic extraction of hyperspectral information of the camellia oleifera fruits. According to the method, through the innovative CA-TransUNet + + image segmentation model, the camellia oleifera fruits can be rapidly and efficiently segmented, the hyperspectral information of the camellia oleifera fruits can be extracted, the linear decision coefficient (R2) of the method and a manual extraction result can reach 99.03%, and the processing time of a single fruit image is about 1-2 seconds. According to the method, the hyperspectral data of the camellia oleifera fruits can be efficiently and accurately acquired in a natural scene.

The invention belongs to the technical field of mineral engineering and information, and discloses a hydraulic transmission type coal mine landslide speed control device and a test method. The method comprises the steps of prototype analysis and similarity coefficient determination; preparing and designing similar materials; material characteristic inspection: detecting physical and mechanical characteristics of the material; calculating test parameters, and calculating an expected speed, an acceleration distance and a parking height by using mathematical and numerical methods according to a similarity theory and a landslide dynamics principle; arranging sensors, adjusting the angle of the material box, carrying out a landslide mass model test, and cleaning and maintaining the material box. The test method provided by the invention has the characteristics of simplicity in operation, low cost and high repeatability, and is convenient for carrying out experimental research on landslide mass speed control under diversified geological conditions. According to the landslide mass speed control device and the test method thereof, the efficiency and safety of landslide prevention and control work can be remarkably improved, and damage of landslide disasters to the human society and the natural environment is reduced.

The invention relates to the technical field of biological control of plant diseases, in particular to application of a bacillus atrophaeus strain and a preparation thereof to control wheat gibberellic disease caused by gibberellic maize. The preservation number of the strain is CGMCC (China General Microbiological Culture Collection Center) No.29799, and the strain is classified and named as the bacillus atrophaeus strain HHQGTS13-1 (Bacillus atrophaeus HHQGTS13-1). The bacillus atrophaeus strain HHQGTS13-1 is wide in application range to natural environment conditions such as temperature and pH, and has the capability of antagonizing fusarium maydis when the temperature is 10-45 DEG C and the pH value is 4-10. The bacillus atrophaeus strain HHQGTS13-1 can be used for obviously inhibiting the growth of fusarium maydis hyphae and enabling the hyphae to be deformed; the antagonistic bacillus HHQGTS13-1 strain has an obvious inhibition effect on spore germination of fusarium maydis, the spore germination inhibition rate is 97.10%, the prevention and treatment effect of the antagonistic bacillus HHQGTS13-1 strain fermentation liquor after wheat is inoculated with fusarium maydis pathogenic bacteria is 63.43%, and the antagonistic bacillus HHQGTS13-1 strain has good potential of preventing and treating plant diseases caused by fusarium maydis.

The invention relates to the technical field of building design, in particular to an ancient building visual color matching method, which comprises the following steps of: 1, acquiring multi-source data; step 2, color feature extraction; 3, constructing a historical color knowledge base; step 4, constructing a color matching model; and step 5, performing three-dimensional visual rendering. According to the historic building visual color matching method, qualitative analysis of'regional culture-natural environment 'is converted into quantitative collection of multispectral images and three-dimensional point clouds, and spatial accurate positioning of color features is achieved; a standardized knowledge base containing historical periods and technologies is constructed, and the fragmentation problem of traditional color matching experience is solved; through physical realistic rendering, the method is expanded to color simulation of the ancient building under different climate conditions, and the recovery credibility is improved.

The invention discloses environment-friendly cassava cat litter and a preparation method thereof, and belongs to the technical field of pet supplies, and the environment-friendly cassava cat litter is prepared from the following raw materials in parts by weight: 45-55 parts of cassava starch, 20-30 parts of cassava peel, 8-15 parts of corn starch, 8-12 parts of water hyacinth fiber, 5-10 parts of bamboo fiber, 2-4 parts of propolis and 1.5-3.0 parts of mussel mucin. The raw materials are subjected to step-by-step synergistic enzymolysis and step-by-step fermentation to obtain the environment-friendly cassava cat litter. According to the mode, natural raw materials are combined, and the preparation process of step-by-step enzymolysis and step-by-step fermentation is adopted, so that the antibacterial performance and water absorption performance of the cat litter are improved, the defecation comfort and cleanliness of pet cats are improved, sanitation and health of pets and family environments are guaranteed, meanwhile, the product can be completely degraded in the natural environment after being used, and the environment is protected. The cat litter does not generate permanent solid waste like bentonite and silica gel cat litter, and is very environment-friendly.

The invention provides a rare earth complex as well as a preparation method and application thereof. The chemical general formula of the rare earth complex is (Ln < 1x > Ln < 2y > Ln < 31-x-y >) (A) m (B) n, the rare earth complex provided by the invention has a self-assembly behavior, spherical nanoparticles can be formed through molecular aggregation, under ultraviolet irradiation, internal ligand molecules are better protected, the photobleaching process of the rare earth complex under natural conditions is slowed down, and the rare earth complex has better stability and higher weather resistance in the natural environment.

The invention provides an assembly type frame beam slope protection structure which comprises a plurality of anchor cables used for being inserted into the ground, the bottom ends of the anchor cables are provided with gyro-shaped plugs, the side walls of the plugs are provided with threads, reinforcing structures are arranged between the anchor cables inserted into the ground and soil, and the ends, located outside the ground, of the anchor cables are provided with clamping assemblies. The adjacent clamping assemblies are connected through the cross beams or the longitudinal beams. And green plants are planted on the large land in the lattices enclosed by the cross beams and the longitudinal beams. According to the assembly type frame beam slope protection structure, the structural design facilitates rapid construction on an exposed slope, the whole construction process has the advantages of being low in manufacturing cost, saving resources and not damaging the natural environment, and meanwhile the technical advantage of reinforcing and stabilizing the slope is achieved.

The invention discloses a device and method for simulating the freezing and thawing cycle process of collapsible loess in the natural environment, and belongs to the technical field of geotechnical engineering.The device comprises a test box provided with a sample groove, a rainfall simulation system is arranged on the upper portion in the test box, an underground water seepage simulation system is arranged on the lower portion in the test box, and the sample groove is connected with a loading system; a weighing system is arranged at the bottom in the test box, the weighing system is connected with an underground water seepage simulation system, a settlement and internal damage monitoring system is arranged between the weighing system and the rainfall simulation system, and a freezing and thawing circulation system is arranged on the inner side wall of the test box. According to the invention, the natural environment of the loess plateau area can be simulated, and the strength change of the strong salinized soil in the dry-wet process can be tested and researched under the combined action of various factors such as rainfall, load, underground water seepage and freeze-thaw cycle.

The invention provides a wetland ecological restoration effect comprehensive evaluation method and system, and belongs to the technical field of big data analysis. According to the method, real-time data of multi-dimensional ecological elements such as water turbidity, vegetation coverage density and soil acidity and alkalinity are collected, a multi-dimensional element correlation matrix based on time sequence correlation is constructed, and the dynamic change frequency of each element is captured. Core influence factors are screened by quantifying the contribution degree of each element to ecological restoration, weight distribution corresponding to clustered element clusters is determined, and then an accurate quantitative score is generated and mapped into a clear restoration condition level through multiplication and summation of inter-cluster correlation coefficients and weights item by item. Meanwhile, an evolution track is compared and analyzed by combining historical time sequence data, and the weight is dynamically adjusted to ensure that evaluation adapts to an actual repair process. The comprehensive, dynamic and accurate evaluation of the wetland ecological restoration effect is realized, scientific support is provided for the accurate adjustment of the restoration strategy, and the fine management of the wetland and the sustainable development of the natural environment are guaranteed.

The invention discloses a camellia oleifera multi-target intelligent detection method and system based on dynamic illumination adaptive adjustment, and the method comprises the steps: carrying out the region segmentation preprocessing of a to-be-detected camellia oleifera image, and generating a multi-region segmented camellia oleifera image; inputting the multi-region segmented camellia oleifera image into a camellia oleifera fruit multi-target recognition immune algorithm, and performing light intensity analysis on the multi-region segmented camellia oleifera image by a trained preference multi-target module; wherein the preference multi-target module is used for carrying out target identification on form color values of camellia oleifera fruits under different illumination conditions as preference data; and according to a light intensity analysis result output by the trained preference multi-target module, obtaining a recognition result of the camellia oleifera fruit in the camellia oleifera image to be detected. According to the method, the efficiency is ensured and the speed is increased in dynamic illumination recognition, and an effective solution is provided for camellia oleifera fruit recognition in a natural environment.

The invention provides a method and a device for efficiently proliferating sepiella maindroni by combining grazing and raising, and belongs to the field of aquatic animal proliferation. An efficient breeding method for sepiella maindroni integrating grazing and breeding comprises the following steps that an appropriate sea area is selected, fertilized eggs are bred in a breeding facility laid in the downstream direction of a normal fish breeding net cage, namely an empty net cage containing an artificial floating reef, the periphery of the empty net cage is provided with an algae-mussel flow blocking ecological rope, and a cover net is arranged above the empty net cage; the newly hatched cuttlefish can stay in the proliferation facility empty net cage for a long time due to the characteristics of loving reefs and drilling the net and strong space awareness, and slowly escape into natural water after gradually adapting to the proliferation environment. According to the proliferation method, cuttlefishes gradually adapt to the natural environment of the sea area, meanwhile, cuttlefish larvae are well protected enough in the fragile incubation initial stage through protection measures such as net cages, and therefore the proliferation survival rate and the maintenance efficiency are improved, and efficient proliferation is achieved.

The invention discloses a soil solidification effect detection and analysis system and method, and relates to the field of soil solidification effect detection.The soil solidification effect detection and analysis method comprises the steps that based on the sedimentation characteristics of a solidification material, soil is divided into a bottom sedimentation sudden change zone, a middle sedimentation gradual change zone and a top sedimentation stable zone in the depth direction, and the minimum operation thickness of a sampling tool serves as the reference layer thickness; dividing non-equidistant sampling layers according to different multiples in each settlement zone to intercept columnar soil samples; performing an initial dynamic load test on the original soil sample, then performing circulating saturated water drying treatment on the same soil sample, and applying the completely same dynamic load mode again; a water circulation effect in a natural environment is simulated by performing vacuum water saturation and constant-temperature drying circulation treatment on a soil sample for multiple times and combining a dynamic load test after water damage. Through non-equal-interval stratified sampling and multi-round dry-wet cycle testing, stratified dynamic and high-precision quantitative evaluation of the water damage resistance of soil solidification is achieved.

The invention discloses a forest fire intelligent monitoring and early warning method and system based on a multi-modal large model, and the method comprises the steps: carrying out the fire recognition and environment analysis based on a multi-modal data fusion mechanism of the multi-modal large model in combination with multi-source data collected by an unmanned plane; an auxiliary early warning solution is automatically generated for the fire by combining a multi-modal model with a forest ranger inspection report, an unmanned aerial vehicle inspection video and a fire analysis result, and emergency processing suggestions are provided; massive multi-source heterogeneous data in the forest fire intelligent monitoring and early warning system is efficiently stored, managed and retrieved, the distributed training and reasoning process of a multi-modal large model is optimized, and it is ensured that the system can achieve rapid and accurate fire monitoring and early warning in a complex natural environment. According to the invention, full-process automatic management and comprehensive analysis from data acquisition, fire monitoring to analysis and decision making are realized, and problems of insufficient intelligent identification capability, high false alarm rate and low data integration analysis efficiency in the existing forest fire monitoring and early warning process are solved.