34results about How to "Early forecast" patented technology

The invention relates to a method and system for predicting the social network information transmission trend. The method includes the steps that information data and user date in a social network are obtained, and a user categorical distribution vector is calculated by means of the user data; normalization processing is carried out on the information data; smoothing processing is conducted on the normalized information data through a moving average method, a Diffusion-Info user categorical distribution vector is combined to figure out predicted points of the information transmission trend, and an information transmission trend line is drawn; a plurality of basic information transmission curves obtained through a K-SC algorithm and the information transmission trend line are fitted to obtain a follow-up trend line of the information transmission trend prediction line. According to the method and system, information transmission capacity can be estimated as soon as possible, hysteresis of a traditional method is reduced, and assistance is provided for timely pushing of information and timely control of public opinions of the social network; meanwhile, when the system operates, cost of an internal storage is low, and high efficiency, independence and transportability are achieved.

The invention relates to the technical field of sensor detection, in particular to an online monitoring system for particle in liquid oil. The online monitoring system comprises a detection cavity, aparticle sensor, a ferromagnetic particle sensor and a processor, the detection cavity is used for allowing the liquid oil to be detected, the particle sensor and the ferromagnetic particle sensor arearranged in the detection cavity and connected with the processor, and the processor is used for acquiring a particle detection result according to output signals of the particle sensor and the ferromagnetic particle sensor. The system can monitor various particle parameters at the same time, so that monitoring index is increased, more basis is provided for oil change opportunity, ability of sensing equipment running state is improved, and stable running of equipment is ensured.

The invention relates to an easily-occurring disease prediction system based on a merdian-collateral energy balance value, which comprises a main and collateral channels acquisition module, a pretreatment module, an easily-occurring disease prediction module, a prediction result processing module and a client terminal, wherein the main and collateral channels acquisition module acquires and analyzes to obtain the energy balance value of twelve main and collateral channels, and transmit to the preprocessing module. The preprocessing module comprises an energy area dividing unit, a merdian-collateral risk pattern map unit and a storage unit, wherein a merdian-collateral risk pattern map table established by the merdian-collateral risk pattern map unit is used for determining a risk pattern and a risk grade of each main and collateral channels, the storage unit assigns a value to the merdian-collateral risk prediction function fi to form a merdian-collateral risk mode set psi; the easily-occurring disease prediction module establishes a easily-occurring symptom prediction model to form a symptom set phi'; a easily-occurring disease prediction model is established to obtain a prediction function value Ri for the easily-occurring diseases in a disease set omega one by one; the prediction result processing module screens and sorts Ri to form a new easily-occurring disease set omega',and a data report is generated in the client terminal.

The invention discloses a method for predicting bacterial blight of rice by utilizing miRNA 169h genes, belonging to the technical field of biology. The method comprises the following steps: selecting rice to be detected and control rice, wherein the selected control rice is not infected with the bacterial blight but is cultivated with the rice to be detected under the same conditions; respectively separating total miRNA genes in the rice to be detected and the control rice; respectively detecting the expression quantities of the miRNA169h genes in the total miRNA genes in the rice to be detected and the control rice, wherein the sequences of the miRNA169h genes are shown in SEQ ID NO:1 in a sequence table; and judging whether the experiments are successful according to the expression quantities of the miRNA169h genes in the rice to be detected and the control rice and further judging whether a plant to be detected is infected with the bacterial blight if the experiments are successful. The prediction method disclosed by the invention achieves success, can achieve accurate prediction a few days before the bacterial blight of rice appears and has the effects of gaining time for early prevention and treatment and reducing the rice loss caused by the bacterial blight.

The invention discloses a method using miRNA399j gene for prediction of bacterial leaf blight of rice, and belongs to the field of biotechnology. The method comprises the following steps: rice to be measured and control rice are selected, the selected the control rice is not infected with the bacterial leaf blight and is cultivated in the same condition with the rice to be measured; total miRNA genes in the rice to be measured and the control rice are separated respectively; the expression amounts of the miRNA399j gene in the total miRNA genes in the rice to be measured and the control rice are detected respectively; the miRNA399j gene sequence is as shown in SEQ ID NO:1 in a sequence table; and according to the expression amounts of the miRNA399j gene in the total miRNA genes in the rice to be measured and the control rice, whether the experiment is successful is judged, and if the experiment is successful, whether the plant to be measured is infected with the bacterial leaf blight is further determined. The prediction method achieves a success, can accurately predict a few days before the bacterial leaf blight of rice, wins time for the early prevention and treatment, and reduces the loss caused by the bacterial leaf blight of rice.

The invention discloses a method for forecasting bacterial leaf blight of paddy rice by utilizing miRNA396c gene at early stage, and belongs to the technical field of biology. The method comprises the following steps: selecting to-be tested paddy rice and control paddy rice, wherein the selected control paddy rice is paddy rice which is not infected by bacterial leaf blight and is cultivated under same conditions with the to-be tested paddy rice; respectively separating total miRNA gene of the to-be tested paddy rice and the control paddy rice; respectively detecting the expression level of miRNA396c gene in the total miRNA gene of the to-be tested paddy rice and the control paddy rice, wherein the sequence of the miRNA396c gene is shown as SEQ ID NO: 1; and determining whether the experiment is successful according to the expression level of miRNA396c gene in the to-be tested paddy rice and the control paddy rice, if successful, further determining whether the to-be tested plant is infected by bacterial leaf blight. The provided prediction method is successful, is capable of accurately performing forecast several days before paddy rice has symptoms of bacterial leaf blight, wins time for early prevention and early controlling, and helps to reduce loss of paddy rice caused by bacterial leaf blight.

The invention discloses a method for predicting rice bacterial blight with miRNA169h gene, and belongs to the field of biotechnology. The method comprises the following steps: selecting the rice to be tested and the control rice, wherein the selected control rice is not infected with bacterial blight but cultivated under the same conditions as the rice to be tested; isolating the rice to be tested and the rice to be tested respectively The total miRNA gene in the control rice; respectively detect the expression level of the miRNA169h gene in the total miRNA gene in the rice to be tested and the control rice, the sequence of the miRNA169h gene is as shown in SEQ ID NO:1 in the sequence table According to the expression levels of the miRNA169h gene in the rice to be tested and the control rice, judge whether the experiment is successful, and if successful, further determine whether the plant to be tested is infected with bacterial blight. The prediction method provided by the invention is successful, and can realize accurate forecast several days before the rice bacterial blight occurs, gaining time for early prevention and early treatment, and reducing the loss caused by the bacterial blight to rice.

The invention discloses a method using miRNA395k gene for prediction of bacterial leaf blight of rice, and belongs to the field of biotechnology. The method comprises the following steps: rice to be measured and control rice are selected, the selected the control rice is not infected with the bacterial leaf blight and is cultivated in the same condition with the rice to be measured; total miRNA genes in the rice to be measured and the control rice are separated respectively; the expression amounts of the miRNA395k gene in the total miRNA genes in the rice to be measured and the control rice are detected respectively; the miRNA395k gene sequence is as shown in SEQ ID NO:1 in a sequence table; and according to the expression amounts of the miRNA395k gene in the total miRNA genes in the rice to be measured and the control rice, whether the experiment is successful is judged, and if the experiment is successful, whether the plant to be measured is infected with the bacterial leaf blight is further determined. The prediction method achieves a success, can accurately predict a few days before the bacterial leaf blight of rice, wins time for the early prevention and treatment, and reduces the loss caused by the bacterial leaf blight of rice.

The invention discloses a method for forecasting bacterial leaf blight of paddy rice by utilizing miRNA396c gene at early stage, and belongs to the technical field of biology. The method comprises the following steps: selecting to-be tested paddy rice and control paddy rice, wherein the selected control paddy rice is paddy rice which is not infected by bacterial leaf blight and is cultivated under same conditions with the to-be tested paddy rice; respectively separating total miRNA gene of the to-be tested paddy rice and the control paddy rice; respectively detecting the expression level of miRNA396c gene in the total miRNA gene of the to-be tested paddy rice and the control paddy rice, wherein the sequence of the miRNA396c gene is shown as SEQ ID NO: 1; and determining whether the experiment is successful according to the expression level of miRNA396c gene in the to-be tested paddy rice and the control paddy rice, if successful, further determining whether the to-be tested plant is infected by bacterial leaf blight. The provided prediction method is successful, is capable of accurately performing forecast several days before paddy rice has symptoms of bacterial leaf blight, wins time for early prevention and early controlling, and helps to reduce loss of paddy rice caused by bacterial leaf blight.

The invention relates to an easily-occurring disease prediction system based on a merdian-collateral energy balance value, which comprises a main and collateral channels acquisition module, a pretreatment module, an easily-occurring disease prediction module, a prediction result processing module and a client terminal, wherein the main and collateral channels acquisition module acquires and analyzes to obtain the energy balance value of twelve main and collateral channels, and transmit to the preprocessing module. The preprocessing module comprises an energy area dividing unit, a merdian-collateral risk pattern map unit and a storage unit, wherein a merdian-collateral risk pattern map table established by the merdian-collateral risk pattern map unit is used for determining a risk pattern and a risk grade of each main and collateral channels, the storage unit assigns a value to the merdian-collateral risk prediction function fi to form a merdian-collateral risk mode set psi; the easily-occurring disease prediction module establishes a easily-occurring symptom prediction model to form a symptom set phi'; a easily-occurring disease prediction model is established to obtain a prediction function value Ri for the easily-occurring diseases in a disease set omega one by one; the prediction result processing module screens and sorts Ri to form a new easily-occurring disease set omega',and a data report is generated in the client terminal.

The invention discloses a method using miRNA408 gene for prediction of bacterial leaf blight of rice, and belongs to the field of biotechnology. The method comprises the following steps: rice to be measured and control rice are selected, the selected the control rice is not infected with the bacterial leaf blight and is cultivated in the same condition with the rice to be measured; total miRNA genes in the rice to be measured and the control rice are separated respectively; the expression amounts of the miRNA408 gene in the total miRNA genes in the rice to be measured and the control rice are detected respectively; the miRNA408 gene sequence is as shown in SEQ ID NO:1 in a sequence table; and according to the expression amounts of the miRNA408 gene in the total miRNA genes in the rice to be measured and the control rice, whether the experiment is successful is judged, and if the experiment is successful, whether the plant to be measured is infected with the bacterial leaf blight is further determined. The prediction method achieves a success, can accurately predict a few days before the bacterial leaf blight of rice, wins time for the early prevention and treatment, and reduces the loss caused by the bacterial leaf blight of rice.

The invention discloses a method using miRNA166 b gene for prediction of bacterial leaf blight of rice, and belongs to the field of biotechnology. The method comprises the following steps: rice to be measured and control rice are selected, the selected the control rice is not infected with the bacterial leaf blight and is cultivated in the same condition with the rice to be measured; total miRNA genes in the rice to be measured and the control rice are separated respectively; the expression amounts of the miRNA166 b gene in the total miRNA genes in the rice to be measured and the control rice are detected respectively; the miRNA166 b gene sequence is as shown in SEQ ID NO:1 in a sequence table; and according to the expression amounts of the miRNA166 b gene in the total miRNA genes in the rice to be measured and the control rice, whether the experiment is successful is judged, and if the experiment is successful, whether the plant to be measured is infected with the bacterial leaf blight is further determined. The prediction method achieves a success, can accurately predict a few days before the bacterial leaf blight of rice, wins time for the early prevention and treatment, and reduces the loss caused by the bacterial leaf blight of rice.

The invention relates to a method and system for predicting the social network information transmission trend. The method includes the steps that information data and user date in a social network are obtained, and a user categorical distribution vector is calculated by means of the user data; normalization processing is carried out on the information data; smoothing processing is conducted on the normalized information data through a moving average method, a Diffusion-Info user categorical distribution vector is combined to figure out predicted points of the information transmission trend, and an information transmission trend line is drawn; a plurality of basic information transmission curves obtained through a K-SC algorithm and the information transmission trend line are fitted to obtain a follow-up trend line of the information transmission trend prediction line. According to the method and system, information transmission capacity can be estimated as soon as possible, hysteresis of a traditional method is reduced, and assistance is provided for timely pushing of information and timely control of public opinions of the social network; meanwhile, when the system operates, cost of an internal storage is low, and high efficiency, independence and transportability are achieved.

The invention discloses a method for accurately forecasting bacterial leaf blight of paddy rice at early stage by utilizing miRNA162b gene, and belongs to the technical field of biology. The method comprises the following steps: selecting to-be tested paddy rice and control paddy rice, wherein the selected control paddy rice is paddy rice which is not infected by bacterial leaf blight and is cultivated under same conditions with the to-be tested paddy rice; respectively separating total miRNA gene of the to-be tested paddy rice and the control paddy rice; respectively detecting the expression level of miRNA162b gene in the total miRNA gene of the to-be tested paddy rice and the control paddy rice, wherein the sequence of the miRNA162b gene is shown as SEQ ID NO: 1; and determining whether the experiment is successful according to the expression level of miRNA162b gene in the to-be tested paddy rice and the control paddy rice, if successful, further determining whether the to-be tested plant is infected by bacterial leaf blight. The provided prediction method is successful, is capable of accurately performing forecast several days before paddy rice has symptoms of bacterial leaf blight, wins time for early prevention and early controlling, and helps to reduce loss of paddy rice caused by bacterial leaf blight.

The invention discloses a method for accurately forecasting bacterial leaf blight of paddy rice at early stage by utilizing miRNA167c gene, and belongs to the technical field of biology. The method comprises the following steps: selecting to-be tested paddy rice and control paddy rice, wherein the selected control paddy rice is paddy rice which is not infected by bacterial leaf blight and is cultivated under same conditions with the to-be tested paddy rice; respectively separating total miRNA gene of the to-be tested paddy rice and the control paddy rice; respectively detecting the expression level of miRNA167c gene in the total miRNA gene of the to-be tested paddy rice and the control paddy rice, wherein the sequence of the miRNA167c gene is shown as SEQ ID NO: 1; and determining whether the experiment is successful according to the expression level of miRNA167c gene in the to-be tested paddy rice and the control paddy rice, if successful, further determining whether the to-be tested plant is infected by bacterial leaf blight. The provided prediction method is successful, is capable of accurately performing forecast several days before paddy rice has symptoms of bacterial leaf blight, wins time for early prevention and early controlling, and helps to reduce loss of paddy rice caused by bacterial leaf blight.

The invention discloses a method for predicting rice bacterial blight with miRNA393a gene, and belongs to the field of biotechnology. The method comprises the following steps: selecting the rice to be tested and the control rice, wherein the selected control rice is not infected with bacterial blight but cultivated under the same conditions as the rice to be tested; isolating the rice to be tested and the rice to be tested respectively The total miRNA gene in the control rice; respectively detect the expression level of the miRNA393a gene in the total miRNA gene in the rice to be tested and the control rice, the sequence of the miRNA393a gene is as shown in SEQ ID NO:1 in the sequence listing According to the expression levels of the miRNA393a gene in the rice to be tested and the control rice, judge whether the experiment is successful, and if successful, further determine whether the plant to be tested is infected with bacterial blight. The prediction method provided by the invention is successful, and can realize accurate forecast several days before the rice bacterial blight occurs, gaining time for early prevention and early treatment, and reducing the loss caused by the bacterial blight to rice.

The invention relates to a curative effect prediction system for MTX treatment of JIA before administration and an establishment method thereof. According to the establishing method, the characteristic variable subset of the detection items of the JIA patient is screened out, the machine learning algorithm is used for establishing the curative effect prediction system for the characteristic variable subset, the AUC reaches 97%, the corresponding prediction sensitivity, specificity and accuracy are all 90% or above, and the prediction performance is remarkably improved compared with a system established through a traditional method. According to the curative effect prediction system, expensive genotype detection is not needed during curative effect prediction, prediction of the curative effect model can be completed only through conventional necessary examination items of a patient, extra payment detection is not needed, the patient does not need to wait for a long time, and the curative effect can be predicted only after conventional detection is completed on the same day of treatment. After a doctor sees a prediction result in time, a drug administration decision can be made to apatient immediately. The curative effect prediction system for MTX treatment of JIA before administration established by the establishment method is an effective tool which is simple, convenient, easyto use, efficient and capable of accurately predicting the MTX curative effect of a patient at an early stage.

The invention relates to a nondestructive detection system and method for pulsed magnetic flux leakage defects and stresses, belonging to the field of nondestructive detection. The system comprises a signal generator, a power amplifier, an excitation coil, a Hall sensor, a signal amplification circuit, a data acquisition card and a computer. In the invention, on the basis of pulsed magnetic flux leakage detection, signal processing is performed on a ferromagnetic material in segments according to a transient ascent phase of pulse excitation and a continuous high level phase after the rise, and the separation of stress signals and defect signals is realized; as signal characteristic extraction and data fusion are performed respectively, the simultaneous on-line detection of defects, stresses and microstructure states of a surface and a subsurface of the ferromagnetic material is realized, and the judgment of hidden defects and the estimation of unformed defects of the ferromagnetic material are realized. The nondestructive detection system can work reliably for a long term, has the advantages of high sensitivity, high antijamming capability and high response speed, and is free fromthe influences of a medium such as oil / water pollution and the like.

The invention discloses a method for predicting rice bacterial blight by using miRNA827 gene, and belongs to the field of biotechnology. The method comprises the following steps: selecting the rice to be tested and the control rice, wherein the selected control rice is not infected with bacterial blight but cultivated under the same conditions as the rice to be tested; isolating the rice to be tested and the rice to be tested respectively The total miRNA gene in the control rice; respectively detect the expression level of the miRNA827 gene in the total miRNA gene in the rice to be tested and the control rice, the sequence of the miRNA827 gene is as SEQ? ID? Shown in NO: 1; According to the expression levels of the miRNA827 gene in the rice to be tested and the control rice, judge whether the experiment is successful, and if successful, further determine whether the plant to be tested is infected with bacterial blight. The prediction method provided by the invention is successful, and can realize accurate forecast several days before the rice bacterial blight occurs, gaining time for early prevention and early treatment, and reducing the loss caused by the bacterial blight to rice.

The invention discloses an electronic signal displaying controller with switching and manual reset functions. The controller comprises a controller shell. The controller shell is provided with an upper wiring panel, a display panel and a lower wiring panel, and an MCU processing unit is arranged in the controller shell, is powered by being connected with an alternating current to 12 V voltage module and a 12 V to 3.3 V voltage module, is connected to a high-precision AD of the MCU processing unit by being connected with an operation amplifier amplifying unit through a sensing element, is connected to a control module through a key input module and is connected with a display output module and a relay output module. Data revaluation is carried out through an amplifier and collection of the high-precision AD of the MCU processing unit; the actual value and the alarm value are displayed through two LEDs, and conditions possibly happening are predicted as soon as possible; a module-type power supply and a pi-type filter circuit are good in anti-interference performance, switching reset can be achieved in a plurality of positions, and reset switching can be conveniently carried out.

The invention discloses a method for early and accurate prediction of rice bacterial blight by using miRNA167c gene, and belongs to the field of biotechnology. The method comprises the following steps: selecting the rice to be tested and the control rice, wherein the selected control rice is not infected with bacterial blight but cultivated under the same conditions as the rice to be tested; isolating the rice to be tested and the rice to be tested respectively The total miRNA gene in the control rice; respectively detect the expression level of the miRNA167c gene in the total miRNA gene in the rice to be tested and the control rice, the sequence of the miRNA167c gene is as shown in SEQ ID NO:1 in the sequence table According to the expression levels of the miRNA167c gene in the rice to be tested and the control rice, judge whether the experiment is successful, and if successful, further determine whether the plant to be tested is infected with bacterial blight. The prediction method provided by the invention is successful, and can realize accurate forecast several days before the rice bacterial blight occurs, gaining time for early prevention and early treatment, and reducing the loss caused by the bacterial blight to rice.

The invention discloses a method for predicting rice bacterial blight by using miRNA399j gene, and belongs to the field of biotechnology. The method comprises the following steps: selecting the rice to be tested and the control rice, wherein the selected control rice is not infected with bacterial blight but cultivated under the same conditions as the rice to be tested; isolating the rice to be tested and the rice to be tested respectively The total miRNA gene in the control rice; respectively detect the expression level of the miRNA399j gene in the total miRNA gene in the test rice and the control rice, the sequence of the miRNA399j gene is as SEQ? ID? Shown in NO: 1; According to the expression levels of the miRNA399j gene in the rice to be tested and the control rice, judge whether the experiment is successful, and if successful, further determine whether the plant to be tested is infected with bacterial blight. The prediction method provided by the invention is successful, and can realize accurate forecast several days before the rice bacterial blight occurs, gaining time for early prevention and early treatment, and reducing the loss caused by the bacterial blight to rice.

The invention discloses a method using miRNA397b gene for prediction of bacterial leaf blight of rice, and belongs to the field of biotechnology. The method comprises the following steps: rice to be measured and control rice are selected, the selected the control rice is not infected with the bacterial leaf blight and is cultivated in the same condition with the rice to be measured; total miRNA genes in the rice to be measured and the control rice are separated respectively; the expression amounts of the miRNA397b gene in the total miRNA genes in the rice to be measured and the control rice are detected respectively; the miRNA397b gene sequence is as shown in SEQ ID NO:1 in a sequence table; and according to the expression amounts of the miRNA397b gene in the total miRNA genes in the rice to be measured and the control rice, whether the experiment is successful is judged, and if the experiment is successful, whether the plant to be measured is infected with the bacterial leaf blight is further determined. The prediction method provides a success, can accurately predict a few days before the bacterial leaf blight of rice, wins time for the early prevention and treatment, and reduces the loss caused by the bacterial leaf blight of rice.