Objective To detect cadmium in environmental and food samples by graphite furnace atomic absorption spectroscopy （GFAAS） and inductively coupled plasma atomic emission spectroscopy （ICPAES）. Methods An indirect co...Objective To detect cadmium in environmental and food samples by graphite furnace atomic absorption spectroscopy （GFAAS） and inductively coupled plasma atomic emission spectroscopy （ICPAES）. Methods An indirect competitive enzyme-linked immunosorbent assay （IC-ELISA） was developed based on a cadmium-specific monoclonal antibody. IC-ELISA for cadmium in environmental and food samples was evaluated. Results IC-ELISA showed an IC50 of 45.6 μg/L with a detection limit of 1.95 μg/L for cadmium, and showed a mean recovery ranging 97.67%-107.08%. The coefficient of variations for intra- and interassay was 3.41%-6.61% and 4.70%-9.21%, respectively. The correlation coefficient between IC-ELISA and GFAAS was 0.998. Conclusion IC-ELISA can detect and quantify cadmium residue in environmental or food samples.展开更多
In the past several years,various visual object tracking benchmarks have been proposed,and some of them have been used widely in numerous recently proposed trackers.However,most of the discussions focus on the overall...In the past several years,various visual object tracking benchmarks have been proposed,and some of them have been used widely in numerous recently proposed trackers.However,most of the discussions focus on the overall performance,and cannot describe the strengths and weaknesses of the trackers in detail.Meanwhile,several benchmark measures that are often used in tests lack convincing interpretation.In this paper,12 frame-wise visual attributes that reflect different aspects of the characteristics of image sequences are collated,and a normalized quantitative formulaic definition has been given to each of them for the first time.Based on these definitions,we propose two novel test methodologies,a correlation-based test and a weight-based test,which can provide a more intuitive and easier demonstration of the trackers’performance for each aspect.Then these methods have been applied to the raw results from one of the most famous tracking challenges,the Video Object Tracking(VOT)Challenge 2017.From the tests,most trackers did not perform well when the size of the target changed rapidly or intensely,and even the advanced deep learning based trackers did not perfectly solve the problem.The scale of the targets was not considered in the calculation of the center location error;however,in a practical test,the center location error is still sensitive to the targets’changes in size.展开更多
基金supported by the Research Foundation of Science and Technology Project in Guangdong Province of China (No.2003C20409)Science and Technology Project in General Administration of Quality Supervision,Inspection and Quarantine of China(No. 2004IK062)
文摘Objective To detect cadmium in environmental and food samples by graphite furnace atomic absorption spectroscopy （GFAAS） and inductively coupled plasma atomic emission spectroscopy （ICPAES）. Methods An indirect competitive enzyme-linked immunosorbent assay （IC-ELISA） was developed based on a cadmium-specific monoclonal antibody. IC-ELISA for cadmium in environmental and food samples was evaluated. Results IC-ELISA showed an IC50 of 45.6 μg/L with a detection limit of 1.95 μg/L for cadmium, and showed a mean recovery ranging 97.67%-107.08%. The coefficient of variations for intra- and interassay was 3.41%-6.61% and 4.70%-9.21%, respectively. The correlation coefficient between IC-ELISA and GFAAS was 0.998. Conclusion IC-ELISA can detect and quantify cadmium residue in environmental or food samples.
基金Project supported by the National Natural Science Foundation of China(No.61501139)the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology,Weihai(No.2019KYCXJJYB06).
文摘In the past several years,various visual object tracking benchmarks have been proposed,and some of them have been used widely in numerous recently proposed trackers.However,most of the discussions focus on the overall performance,and cannot describe the strengths and weaknesses of the trackers in detail.Meanwhile,several benchmark measures that are often used in tests lack convincing interpretation.In this paper,12 frame-wise visual attributes that reflect different aspects of the characteristics of image sequences are collated,and a normalized quantitative formulaic definition has been given to each of them for the first time.Based on these definitions,we propose two novel test methodologies,a correlation-based test and a weight-based test,which can provide a more intuitive and easier demonstration of the trackers’performance for each aspect.Then these methods have been applied to the raw results from one of the most famous tracking challenges,the Video Object Tracking(VOT)Challenge 2017.From the tests,most trackers did not perform well when the size of the target changed rapidly or intensely,and even the advanced deep learning based trackers did not perfectly solve the problem.The scale of the targets was not considered in the calculation of the center location error;however,in a practical test,the center location error is still sensitive to the targets’changes in size.
