42results about How to "Verify feasibility" patented technology

The invention discloses an oil palm U6 promoter gene and application thereof, and belongs to the technical field of biology. The nucleotide sequence of the promoter gene is shown as SEQ ID NO.1. The oil palm RNA polymerase III type promoter gene, namely the oil palm endogenous U6 promoter gene EgU6, is obtained by cloning in an oil palm genome for the first time, and the promoter gene has high transcriptional activity and can drive downstream fluorescent protein mNeonGreen expression. The candidate oil palm endogenous U6 promoter gene can be provided for subsequently establishing a high-efficiency oil palm gene editing technology system based on a CRISPR / cas9 (Clustered Regularly Interspaced Short Palindromic Repeats / Cas9) system.

This invention provides a fluorinated DSPE-PEG material, its preparation method, and its applications, belonging to the fields of nanomedicine delivery systems and biomedicine. This invention prepares fluorinated DSPE-PEG materials with different fluorination modification rates by fluorinating distearate phosphatidylethanolamine polyethylene glycol amino groups, and uses these materials as carriers to load sangxin (a type of glycerol) to form fluorinated nanomicelles. This invention systematically screens the effect of fluorination modification rate on the performance of the nanomicelles, determines the optimal fluorination modification rate, and confirms that it can overcome the defect of low cellular uptake of PEGylated carriers and enhance the anti-colorectal cancer activity of the loaded drugs. The fluorinated nanomicelles have uniform particle size, good stability, and excellent biocompatibility with the carrier material. This invention provides a new strategy for the efficient delivery of small molecule active ingredients from traditional Chinese medicine and the treatment of colorectal cancer.

The application relates to a high-throughput identification method of lncRNA coding peptides and application thereof, and belongs to the technical field of biology. The method combines a translationomics technology and a protein mass spectrometry technology, takes ribosome footprint sequencing data as a starting point, determines an open reading frame located on an lncRNA gene according to a three-base periodicity rule of a sequencing fragment, further constructs a proteogenomics index after systematic filtration, uses a computational proteomics method to detect an lncRNA translation event, and systematically identifies lncRNA coding peptides on the basis. The method has the characteristics of modularity and strong expandability, can be widely used for various types of proteome data, and can high-throughput identify and quantitatively detect lncRNA coding peptides. The application provides a prediction of molecular typing and prognosis of cancer patients based on an lncRNA coding peptide network model, and provides an important reference basis for precise medication of clinical patients.

The present application belongs to the technical field of residential area extraction, and discloses a large-range remote sensing image rural street-type residential area extraction method and system fusing target detection and visual attention mechanism, which comprises the following steps: generating a residential area candidate area detection frame on a large-range remote sensing image through a YOLOv7 model detection; and performing accurate extraction of the residential area based on the candidate area detection frame by using a PgNet model to obtain a rural residential area on the large-range remote sensing image. The present application combines the candidate mechanism of the target detection technology and the visual attention mechanism method, and roughly removes the vegetation and terrain, which is conducive to the rapid and automatic extraction of the rural residential area and the buildings thereof, and improves the search efficiency. After obtaining the candidate frame, the PgNet efficient extraction mechanism is used, so that the rural street-type residential area can be rapidly and automatically extracted in remote sensing images of different sizes.

The invention discloses a deepwater structure health monitoring method and system. The method comprises the following steps: establishing a discrete model and constructing a unit strain matrix; collecting single-side surface strain data and establishing a mapping relation between single-side surface theoretical strain and node displacement; constructing a unilateral inverse finite element data fitting item comprising a surface strain fitting item and a lateral shear strain penalty item; constructing a geometric guidance hybrid regularization term consisting of a membrane regularization term and a bending regularization term; assembling a global equation to solve full-field displacement; and recovering full-field strain and stress and outputting a monitoring result. The system comprises a data acquisition module, a preprocessing and inverse reconstruction module, a stabilization solving module and a visual output module. According to the full-field response sensing scheme based on unilateral inverse finite element and geometric guidance mixed regularization, stable and high-precision inversion of full-field displacement, strain and stress of the structure can be realized under the condition of only depending on unilateral sparse sensing data, and the dependence of a traditional method on bilateral sensing arrangement is effectively broken through.

Based on the improved grey wolf optimization algorithm, the PMU optimal configuration method for distribution network is proposed. Under the condition of system full observability, the PMU optimal configuration mathematical model is established. Considering the influence of zero injection node and the system observability under single PMU interruption and single line outage, the constraint conditions of the established PMU optimal configuration mathematical model are modified. On the basis of grey wolf optimization algorithm, the population initialization, nonlinear convergence factor and position update weight coefficient are improved. The improved grey wolf optimization algorithm is used to solve the PMU configuration model under different scenarios. The method builds the optimal configuration model under different scenarios to achieve the goal of system full observability, and uses the improved grey wolf optimization algorithm to solve the PMU optimal configuration scheme. Compared with other algorithms, the method has better optimization effect.

The present application relates to a kind of atomizers, including the inertial sensor and signal processor arranged on atomizer, the inertial sensor, signal processor are connected with the drive circuit of atomizer;The signal processor is based on the attitude signal collected by the inertial sensor, it is handled into the regulation and control signal that atomizer can directly respond, the drive circuit real-time adjustment the output of atomizer.The present application also relates to the calibration method of the atomizer.The atomizer of the present application significantly improves the inhalation deposition efficiency and inhalable fraction of atomized drug.

The application discloses a novel polyhydroxyalkanoate (PHA) polymerase (PhaC) which can efficiently polymerize the activated monomer 6-hydroxyhexanoate-CoA (6HHx-CoA) of 6-hydroxyhexanoate (6HHx). The PhaC is co-expressed with a CoA ligase AlkK, and can synthesize poly-epsilon-caprolactone (PCL) from the direct precursor sodium 6-hydroxyhexanoate in a halomonas sp. Halomonas which has deleted endogenous beta-ketothiolase (PhaA), acetoacetyl-CoA reductase (PhaB), PhaC and enoyl-CoA hydratase (FadB).

This invention relates to a method for energy consumption modeling and process parameter optimization in laser cleaning processes, belonging to the field of advanced manufacturing and automation technology. The method includes the following steps: establishing an energy consumption model for the laser cleaning process based on energy consumption analysis of the laser system, robot system, cooling system, and dust removal system; building a real-time power monitoring platform to obtain experimental parameters of the energy consumption model; establishing an energy-oriented laser cleaning process parameter optimization model considering energy efficiency, surface roughness, and surface oxygen content; solving the model using an improved lion herd optimization algorithm; and providing case studies. This invention is simple and practical, and fully considers energy consumption and cleaning quality during modeling, providing excellent support for energy consumption optimization in laser cleaning processes.

The application discloses a kind of power power balance calculation method and system based on machine learning, belong to electric power system optimization scheduling technical field, will deep neural network and optimization calculation be combined, adopt the strategy of integer variable reduction, the operation state of most thermal power units is determined in advance by Seq2Seq-Attention model, the input of model is the relaxation solution of operating state and scene curve data, and the output is the operating state of thermal power unit, so as to reach the effect of improving the calculation speed of power power balance problem, the acceleration effect evaluation index designed and the acceleration effect verification method based on variable time scale scene generation are used to verify the acceleration effect of the fast calculation method, which has high precision and strong practicability.

The utility model discloses a high-power waveguide sealing connection structure for an electron accelerator, which comprises a front straight waveguide, a rear straight waveguide, a flat flange, a double-groove type flange and a metal gasket, and the corresponding end faces of the front straight waveguide and the rear straight waveguide are respectively connected with the flat flange and the double-groove type flange. The flat flange and the double-groove type flange are connected with each other through respective sealing end surfaces; an annular stepped groove is formed in the sealing end face of the double-groove type flange, surrounding edges are arranged inside and outside the stepped groove, the stepped groove comprises a positioning groove and an auxiliary groove, the metal gasket is provided with a protruding annular positioning frame, the metal gasket is arranged between the flat flange and the double-groove type flange in a cushioned mode, and the positioning frame is connected with the positioning groove in a matched mode. According to the utility model, the sealing problem of high-power waveguide installation is solved, good electric contact of the butt joint plane of the two waveguide metal flanges during high-power microwave transmission operation is realized, high-power microwaves are prevented from escaping, vacuum in the waveguide is ensured, and stable transmission of the high-power microwaves is ensured.

This invention discloses a structural thermo-mechanical coupling method and apparatus considering isogeometric analysis, belonging to the field of thermodynamics. The method includes: S1. Establishing an isogeometric NURBS model: providing the basis for expressing geometric and physical fields for thermo-mechanical coupling analysis, achieving seamless integration of CAD and CAE; S2. Calculating the transient temperature field based on the central difference method: obtaining the temperature distribution of the structure at different times, providing temperature input for subsequent thermo-mechanical coupling; S3. Transforming the temperature field into equivalent temperature loads: converting the thermal effects caused by temperature changes into equivalent loads identifiable by structural mechanics analysis; S4. Solving the stiffness equation of the structure under the combined action of external forces and temperature: obtaining the displacement matrix of the structural control points; S5. Solving the structural coupling field based on the displacement matrix: obtaining all key physical quantities in the thermo-mechanical coupling field, completing the coupling analysis. This invention can verify the feasibility of applying isogeometric analysis in coupled fields.

The invention discloses a deep-eutectic solvent, preparation thereof and application of the deep-eutectic solvent in recovery of a waste ternary lithium battery positive electrode material. The eutectic solvent is composed of ethylene glycol and lactic acid, and the molar ratio of ethylene glycol to lactic acid is 1: 10-10: 1. According to the method, a new eutectic solvent system is creatively constructed, selective leaching of the lithium element in the positive electrode material of the waste ternary lithium battery can be achieved, the coprecipitation process of key metal precursors such as nickel, cobalt and manganese is synchronously promoted, high-valued circulation and utilization of the waste ternary lithium battery are promoted, and the method is suitable for industrial production. The complex process of traditional multi-metal step-by-step separation is avoided, and the operation steps are simplified. In addition, the eutectic solvent can be recycled for more than five times, so that the battery recycling cost is reduced. The recycling method provided by the invention also greatly widens the separation and recycling ways of valuable metals in the waste batteries, and shows wide application potential and important value in the field of resource recycling.

An MIMO array sparse rapid design method of a fuzzy function generator based on deep learning comprises the following steps: firstly, directly learning a fuzzy function mapping relation corresponding to virtual array configuration and an incident angle by using a deep learning model so as to replace a traditional analysis fuzzy function calculation process depending on a manifold matrix; and then performing efficient performance evaluation on the candidate sparse array based on the fuzzy function generator, and obtaining a sparse array structure meeting the requirements of high resolution and low sidelobe in combination with an optimization strategy. By means of the technology, acceleration of more than 35 times can be achieved on the premise of not explicitly calculating the fuzzy function, the fuzzy function prediction root mean square error (RMSE) lower than 0.1 is kept, and therefore the sparse array design time is greatly shortened. Experiments on a 2T4R K-band MIMO radar prove that the designed array achieves 10 dB sidelobe level in a 100-degree field of view, the angular resolution is improved by about 32.8%, and the effectiveness and engineering application value of the method in high-resolution MIMO sparse array design are proved.

The application discloses a control method of structural vibration based on a controller saturation lower band active mass damper, and successfully reduces the vibration of a building structure by introducing an active mass damper and applying a control strategy. In order to meet the control input constraint and performance requirements, a state feedback optimal control law under the controller saturation is proposed by using a linear matrix inequality method; example analysis shows that the proposed control strategy can realize the stability of the closed-loop system and play the best performance, while reducing the control energy consumption and the floor level disturbance; compared with the case without considering the controller saturation, the proposed controller has smaller gain, reduces the energy consumption, and shows better anti-interference performance; numerical examples verify the effectiveness and feasibility of the proposed controller within the saturation limit; the application provides a new idea and method for solving the actual building structure control problem, and has important theoretical significance and practical application value.

The application discloses a design method of a longitudinal-bending ultrasonic vibration assisted deep hole drilling device, which comprises the following steps: selecting a working frequency of the longitudinal-bending ultrasonic vibration assisted deep hole drilling device and materials of each part of the device; sequentially performing transducer design to determine the length and diameter of a front cover plate, a middle cover plate and a rear cover plate and the position of a piezoelectric sheet; performing amplitude rod design to determine the length and diameter of each section of the amplitude rod; constructing a geometric model according to the size of the transducer and the amplitude rod, a bolt pre-tightening structure and a connecting structure of a tool and the device, the device and a machine tool; outputting trajectory modeling; and performing structure optimization and frequency degeneration of the longitudinal-bending ultrasonic vibration assisted deep hole drilling device based on finite element simulation. Thus, the general structure design of the double-excitation longitudinal-bending ultrasonic vibration assisted deep hole drilling device is realized, the frequency degeneration of the longitudinal vibration and the bending vibration is achieved and the amplification coefficient reaches the maximum, so that the design problem of the double-excitation longitudinal-bending same-frequency vibration device is solved.

The application discloses a method for fine-grained respiratory interaction based on visual and auditory detection, comprising the following steps: acquiring respiratory parameters based on respiratory types, and constructing a respiratory input method of an interactive vocabulary; based on the respiratory input method of the interactive vocabulary, designing several characteristic parameters of a respiratory vector representing respiratory interaction actions, and acquiring respiratory intensity, respiratory direction, whether inhaling, respiratory time, respiratory frequency, expression information and volume information from the several characteristic parameters; constructing a visual and auditory double-channel detection model, inputting the expression information and the volume information, and completing respiratory detection. The application realizes the recognition of multiple respiratory action characteristic parameters including respiratory action airflow intensity, respiratory airflow direction, respiratory airflow type and the like based on the combination of images and voices.

This invention discloses a zero-space method for pre-set time trajectory tracking and obstacle avoidance of a two-wheeled differential vehicle, belonging to the field of mobile robot navigation and cooperative control technology. It includes: 1) establishing a kinematic model of the two-wheeled differential vehicle and clarifying the mapping relationship between the vehicle's linear velocity, angular velocity, and body motion; 2) constructing a zero-space multi-task priority control framework, defining obstacle avoidance as the highest priority task and trajectory tracking as the second-priority task; 3) integrating the pre-set time control with the second-priority trajectory tracking task, introducing a practical pre-set time gain to design a pre-set time control law, enabling the vehicle to accurately track the trajectory within a preset time; 4) fusing the desired obstacle avoidance velocity with the desired trajectory tracking velocity after zero-space projection, outputting executable linear and angular velocity commands for the vehicle body; and 5) conducting ideal working condition algorithm simulation in MATLAB. This invention effectively improves the system's safety and motion smoothness.

The invention discloses a flexible micro electrical stimulator capable of being wound and adhered to peripheral nerve tracts and a preparation method and application thereof, and relates to the technical field of crossing of neural engineering, bioelectronics and medical instruments. A first insulation layer, a first friction electrode layer, a middle isolation layer, a second friction electrode layer and a second insulation layer are assembled layer by layer; the first insulation layer and the second insulation layer are self-adhesion polyurethane layers, and the first friction electrode layer, the middle isolation layer and the second friction electrode layer are packaged in the first insulation layer and the second insulation layer; the first friction electrode layer is a gold foil, and the surface of the gold foil is electroplated with a PEDOT: PSS plating layer formed by a 3, 4-ethylenedioxythiophene monomer and polystyrene sulfonate; the second friction electrode layer is gold foil or aluminum foil. According to the invention, macro-scale contact-separation type friction power generation is realized through ultrasonic driving, and the device has good output performance, long-term stability and nerve stimulation effect.

This invention discloses a method for determining the radial magnetic gap of an exciter and a method for calculating the magnetic center difference. The method for determining the radial magnetic gap includes the following steps: dividing the upper surfaces of the rotor and stator into four equal parts at 90° intervals; determining the first set of radial magnetic gap distance values; rotating the rotor 180 degrees; measuring the distance between corresponding marks on the horizontal and vertical axes after rotation to obtain the second set of radial magnetic gap distance values; and adjusting the radial magnetic gap if the horizontal or vertical gap adjustment value is greater than or equal to the average gap value X%. The method for calculating the magnetic center difference of the exciter's magnetic force is based on the difference *a* between the sum of the elongations *D* of the motor and blower shafts and the magnetic center offset of the exciter. This method solves the current problem of lacking relevant maintenance techniques for the magnetic gap and magnetic center difference of exciters.

The utility model provides a temperature sensing probe and a refrigerator cold plate temperature sensing device, comprising an optical fiber probe, a probe fixing member and a microwave antenna, the temperature sensing probe is mainly suitable for application scenarios needing to measure sample shell temperature, such as refrigerator cold plate, chip surface temperature and the like; through the structural design of the optical fiber probe and the probe fixing piece, the diamond block containing the NV color center can be in sufficient and stable contact with the sample to be detected, and it is guaranteed that the temperature detection process is effectively implemented. Meanwhile, the utility model provides temperature sensing equipment suitable for monitoring the temperature of the cold plate of the dilution refrigerator, and the application feasibility of the NV color center sensing technology in the field is verified.

The invention discloses an emotion feature auxiliary personality recognition method and system based on multi-task learning. According to the method, a dual-branch network comprising an emotion branch and a personality branch is constructed by loading and preprocessing multi-modal features, emotion tags and personality tags of an MDPE data set; the emotion branch adopts a Transform encoder to model sequence features and outputs an emotion prediction result; the personality branch adopts a multi-layer perceptron to extract personality embedded representation; further, constructing an emotion feature auxiliary module, performing attention weighted pooling on an emotion prediction result to obtain an emotion abstract representation, splicing the emotion abstract representation with a personality embedded representation, and then realizing information fusion through cross attention and a selectable gating mechanism; and finally, obtaining a personality prediction result through residual connection and layer normalization. A joint loss function is designed to coordinate double-task joint training, the model training effect is guaranteed through an optimization algorithm, a learning rate attenuation strategy and an early stop mechanism, and information sharing and collaborative optimization of emotion recognition and personality recognition are achieved.

The application belongs to the technical field of communication, and discloses a stack decoding method, system, device, medium and terminal based on a soft output, which comprises the following steps: creating a structure and a stack and initializing; repeatedly judging the size of the path length in the structure at the top of the stack and the depth of a decoding tree, if the path length in the structure at the top of the stack is smaller than the depth of the decoding tree, recalculating the path metric, and sorting the stack according to the size of the path metric until the path length in the structure at the top of the stack is equal to the depth of the decoding tree, and counting the soft output probability of each decoding result; and correcting the decoding result according to a preset threshold to obtain a final decoding result. The method disclosed by the application can effectively reduce the calculation complexity under the premise of a low signal-to-noise ratio. In the case of (128, 64), compared with the traditional stack decoding, the stack decoding method of the polar adjustment convolution code based on the soft output can reduce the calculation amount by 82%.

The application relates to a method for tracking a main AUV from an AUV based on a sliding mode adaptive control, which decouples the motion of the AUV into horizontal plane motion and longitudinal plane motion, simultaneously considers the influence of non-constant interference and sea current during the motion of the AUV, designs a control law through a sliding mode adaptive control method, and estimates the sea current velocity on line, so as to guide the AUV to the tail of a target AUV to perform distance tracking. Finally, through tracking simulation of linear motion and curve motion of the target AUV respectively, the feasibility of the AUV long-distance guiding and tracking method is verified. Through adaptive control, the influence of parameter error on the stability of the system is eliminated, the sliding mode adaptive control method can estimate the sea current velocity, the system has certain anti-interference ability, and the robustness of the system is also indicated.

The invention relates to the technical field of plant molecular biology, in particular to an establishment method and application of a low-investment and high-yield cotton protoplast separation and instantaneous transformation system, which comprises the following steps: (1) taking 2-week-old cotton true leaves as a material, and carrying out light-proof pretreatment to reduce the chlorophyll content in the leaves so as to reduce the chlorophyll content in the leaves; (2) using extremely low input amount of leaves (not more than 0.1 g), chopping the pretreated leaves, putting the chopped leaves into optimized enzymatic hydrolysate, and carrying out enzymolysis for 8 hours under the condition of low-speed oscillation at 27-28 DEG C and 50 rpm; and (3) terminating enzymolysis, filtering by an optimization device, centrifuging by a two-time centrifugal method, and washing to obtain the purified protoplast. The cotton leaf protoplast extraction method with extremely low input and high extraction rate and the instantaneous transformation system established by the invention are a system with low loss, high efficiency and wide application, and a feasible scheme is provided for preparing protoplast by utilizing extremely small amount of samples for cotton to analyze gene functions and molecular mechanisms.

The present application proposes a stress inversion and numerical optimization based intrinsic strain field calibration method and system, belonging to the technical field of metal additive manufacturing numerical simulation. The present application solves the problems in the existing strain field calibration method, such as the lack of feedback calibration mechanism based on measured stress, the focus on residual deformation only, the inability to verify the material constitutive model, the poor generalization of intrinsic strain parameters, and the significant deviation between the prediction results of complex components and the actual measurement. The method comprises the following steps: S1: preparing a calibration sample according to the target material; S2: obtaining the measured value of residual stress at the measurement point of the calibration sample; S3: establishing a finite element model of the calibration sample; S4: establishing a target function and performing automatic iterative solution to obtain the optimal solution of the design variable. The system comprises a calibration sample preparation module, a stress measurement module, a modeling module and a design variable solving module.

The present application provides a kind of trace thiabendazole detection method and system of terahertz metamaterial resonance enhancement, the method comprises: based on the characteristic peak frequency of single period structure and thiabendazole, the parameter information of the metamaterial sensor is constructed, and modeling simulation is carried out according to parameter information, to obtain the terahertz metamaterial with L type composite double-peak structure;Preparation thiabendazole sample, and utilize terahertz metamaterial to carry out spectrum collection to thiabendazole sample, to obtain corresponding spectral data;Support vector regression model is constructed, and the optimization algorithm of weighted vector average is integrated, and global optimization of hyperparameter is carried out, to construct corresponding optimization model;According to spectral data and optimization model, corresponding detection model is constructed, and nondestructive testing of trace thiabendazole is realized using detection model.The present application not only realizes high sensitive quantitative analysis to trace thiabendazole residue, also verifies the feasibility and superiority of INFO optimization algorithm in the field of spectral detection.

The invention belongs to the technical field of power system frequency response, and particularly relates to a virtual control unit frequency response credible capacity quantification method. According to the method, multiple types of power distribution side distributed resources are aggregated into a virtual control unit; constructing a distributed resource individual characteristic model, and simulating a running state; establishing a frequency response capacity evaluation model of the resource individuals in combination with the resource characteristics and the operation state; analyzing the selected resource graphical description feasible region to form a frequency response capacity analysis and evaluation method of a resource individual; establishing a virtual control unit frequency response credible capacity quantification model based on confidence and Monte Carlo simulation; and carrying out simulation analysis on the virtual control unit frequency response credible capacity quantitative model, and determining credible capacities under different confidence coefficients. According to the method, frequency modulation resources in shortage of the system can be effectively supplemented, and the frequency response credible capacity of the virtual control unit aggregating various power distribution side distributed resources can be accurately evaluated.

The application discloses a man-machine cooperation assembly planning method considering worker skills and human risk, and the method comprises the following steps: determining the priority relationship, assembly time, worker skill coefficient and occupation repetition index of an assembly task; establishing a mixed integer linear programming model with the minimum tact time, the minimum occupation repetition index and the minimum workstation load balance index as targets; designing a Q-learning artificial bee colony algorithm to solve the mixed integer linear programming model, wherein the algorithm adopts a four-section coding strategy and a decoding mode of minimizing the tact time, a directional search mechanism of action combination of Q-learning is fused in the observation bee stage, and an improved neighborhood search strategy is implemented in the scout bee stage, so that an optimal assembly scheme is output; and generating a man-machine cooperation assembly Gantt chart and a work schematic diagram according to the optimal assembly scheme, so as to guide actual assembly production. The application effectively improves assembly efficiency, reduces the occupational health risk of workers and balances the workstation load.

The application discloses a bearing fault diagnosis method based on multi-source time-frequency feature fusion, and comprises the following steps: acquiring a bearing vibration signal and a rotating speed signal; constructing a bearing fault identification model based on a multi-source time-frequency feature extraction and fusion framework, which is used for identifying the bearing fault; training the bearing fault identification model to obtain a trained bearing fault identification model; and inputting the bearing vibration signal and the rotating speed signal into the trained bearing fault identification model to realize bearing fault classification. Through the combination of multi-source information fusion and an attention mechanism, the application improves feature expression capability and fault identification precision under the premise of ensuring model calculation efficiency, and provides an effective implementation method for bearing fault diagnosis under complex working conditions.