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 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 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 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 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 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 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.