[Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IR...[Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment monitoring data of red tide water were acquired.Then,band ratio method,chlorophyll-a concentration method and secondary filtering method were adopted to extract red tide information.[Result] On October 8,2005,the area of red tide was about 20.0 km2 in Haizhou Bay.There was no red tide in Haizhou bay on May 20,2006.On October 6,2006,large areas of red tide occurred in Haizhou bay,with area of 436.5 km2.On April 22,2009,red tide scattered in Haizhou bay,and its area was about 10.8 km2.[Conclusion] The research would provide technical ideas for the environmental monitoring department of Lianyungang to implement red tide forecast and warning effectively.展开更多
Background: Tuberculosis is a highly infectious disease and India has the highest burden with it. Diagnosis of tuberculosis in many countries is still dependent on microscopy. Although its sensitivity is low in compar...Background: Tuberculosis is a highly infectious disease and India has the highest burden with it. Diagnosis of tuberculosis in many countries is still dependent on microscopy. Although its sensitivity is low in comparison to culture and molecular methods, its sensitivity can still be improved by using fluorescence staining method and processing of samples by homogenization and concentration method. Material and methods: Samples were collected from all newly registered suspected cases of tuberculosis in tertiary care hospital from outward and indoor department during a period of one year. Smears were prepared for Ziehl Neelsen stain and fluorescence stain both before and after homogenization and concentration procedure by 4% NAOH-2.9% sodium citrate method and results of them were interpreted according to RNTCP criteria for grading of sputum samples. All the samples were cultured in liquid culture MGIT system (Mycobacterial Growth Indicator Tube) and results of microscopy were compared with liquid culture taken as gold standard. Data were analyzed by using SPSS software version 16. Result: 350 samples were collected during study period. Out of 350 samples, 48 samples were positive for M. tuberculosis by MGIT system. In comparison with MGIT system, sensitivity of Z N stain for detection of acid fast bacilli was 77% before decontamination procedure, which was increased up to 85.42% after decontamination and concentration process. Sensitivity of fluroscence stain was 85.42% before processing, which was increased up to 91.67% after processing of samples. Conclusion: Sensitivity of smear microscopy can be enhanced by use of fluroscence microscopy and concentration method.展开更多
Water quality sensor networks are promising tools for the exploration of oceans.Some key areas need to be monitored effectively.Water quality sensors are deployed randomly or uniformly,however,and understanding how to...Water quality sensor networks are promising tools for the exploration of oceans.Some key areas need to be monitored effectively.Water quality sensors are deployed randomly or uniformly,however,and understanding how to deploy sensor nodes reasonably and realize effective monitoring of key areas on the basis of monitoring the whole area is an urgent problem to be solved.Additionally,energy is limited in water quality sensor networks.When moving sensor nodes,we should extend the life cycle of the sensor networks as much as possible.In this study,sensor nodes in non-key monitored areas are moved to key areas.First,we used the concentric circle method to determine the mobile sensor nodes and the target locations.Then,we determined the relationship between the mobile sensor nodes and the target locations according to the energy matrix.Finally,we calculated the shortest moving path according to the Floyd algorithm,which realizes the redeployment of the key monitored area.The simulation results showed that,compared with the method of direct movement,the proposed method can effectively reduce the energy consumption and save the network adjustment time based on the effective coverage of key areas.展开更多
基金Supported by Science and Technology Project of Lianyungang City(SH0917)
文摘[Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment monitoring data of red tide water were acquired.Then,band ratio method,chlorophyll-a concentration method and secondary filtering method were adopted to extract red tide information.[Result] On October 8,2005,the area of red tide was about 20.0 km2 in Haizhou Bay.There was no red tide in Haizhou bay on May 20,2006.On October 6,2006,large areas of red tide occurred in Haizhou bay,with area of 436.5 km2.On April 22,2009,red tide scattered in Haizhou bay,and its area was about 10.8 km2.[Conclusion] The research would provide technical ideas for the environmental monitoring department of Lianyungang to implement red tide forecast and warning effectively.
文摘Background: Tuberculosis is a highly infectious disease and India has the highest burden with it. Diagnosis of tuberculosis in many countries is still dependent on microscopy. Although its sensitivity is low in comparison to culture and molecular methods, its sensitivity can still be improved by using fluorescence staining method and processing of samples by homogenization and concentration method. Material and methods: Samples were collected from all newly registered suspected cases of tuberculosis in tertiary care hospital from outward and indoor department during a period of one year. Smears were prepared for Ziehl Neelsen stain and fluorescence stain both before and after homogenization and concentration procedure by 4% NAOH-2.9% sodium citrate method and results of them were interpreted according to RNTCP criteria for grading of sputum samples. All the samples were cultured in liquid culture MGIT system (Mycobacterial Growth Indicator Tube) and results of microscopy were compared with liquid culture taken as gold standard. Data were analyzed by using SPSS software version 16. Result: 350 samples were collected during study period. Out of 350 samples, 48 samples were positive for M. tuberculosis by MGIT system. In comparison with MGIT system, sensitivity of Z N stain for detection of acid fast bacilli was 77% before decontamination procedure, which was increased up to 85.42% after decontamination and concentration process. Sensitivity of fluroscence stain was 85.42% before processing, which was increased up to 91.67% after processing of samples. Conclusion: Sensitivity of smear microscopy can be enhanced by use of fluroscence microscopy and concentration method.
基金This research was funded by the National Natural Science Foundation of China(Grant No.61802010)National Social Science Fund of China(Grant No.19BGL184)+1 种基金Beijing Excellent Talent Training Support Project for Young Top-Notch Team(Grant No.2018000026833TD01)and Hundred-Thousand-Ten Thousand Talents Project of Beijing(Grant No.2020A28).
文摘Water quality sensor networks are promising tools for the exploration of oceans.Some key areas need to be monitored effectively.Water quality sensors are deployed randomly or uniformly,however,and understanding how to deploy sensor nodes reasonably and realize effective monitoring of key areas on the basis of monitoring the whole area is an urgent problem to be solved.Additionally,energy is limited in water quality sensor networks.When moving sensor nodes,we should extend the life cycle of the sensor networks as much as possible.In this study,sensor nodes in non-key monitored areas are moved to key areas.First,we used the concentric circle method to determine the mobile sensor nodes and the target locations.Then,we determined the relationship between the mobile sensor nodes and the target locations according to the energy matrix.Finally,we calculated the shortest moving path according to the Floyd algorithm,which realizes the redeployment of the key monitored area.The simulation results showed that,compared with the method of direct movement,the proposed method can effectively reduce the energy consumption and save the network adjustment time based on the effective coverage of key areas.
