Antibiotic susceptibility testing is a necessary step prior to the treatment of clinical infections. A major concern is the time required to obtain a fast and reliable result. The aim of this work is to use Biospeckle...
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Antibiotic susceptibility testing is a necessary step prior to the treatment of clinical infections. A major concern is the time required to obtain a fast and reliable result. The aim of this work is to use Biospeckle laser in a 15 min assay for an antimicrobial susceptibility test of Ciprofloxacin in serial two-fold dilutions on Escherichia coli K-12 using Venereal Disease Research Laboratory plates. Analysis of images by video edition is performed on a quantitatively selected region of interest, and processed with imageJ-imageDP;and by the construction of time series and analysis with either statistical diagnostics tests or autoregressive integrated moving average (ARIMA) models. Antimicrobial susceptibility tests are also performed for the purpose of quantitative comparison, showing a profile that is comparable to the result obtained with imageJ-imageDP processing after 15 min of antibiotic action. Only the time series of the least affected bacteria (low Ciprofloxacin concentration) behaves in an expected manner, being non-independent and mainly non-linear, non-normal, and heteroscedastic. The most affected bacteria (higher Ciprofloxacin concentration) are non-independent and tend to be linear, normal and heteroscedastic. Adjustment to a linear regression identifies both, the culture medium without bacteria and the most affected bacteria, normality identifies the most affected bacteria and heteroscedasticity-homoscedasticity distinguishes the presence-absence of bacteria, respectively. ARIMA models (1,1,1)(1,0,1)(11) and (4,1,1)(1,1,1)(11) fit the time series of the most affected bacteria while the latter also fits the culture medium without bacteria. The time series of the least affected bacteria are identified by a (7,1,2)(1,0,1)(11) model. The non-linear, non-normal and heteroscedastic behavior of this group is probably responsible for its adjustment to a model with a relatively high parameter. The four methods: diagnostic statistical tests, fitting of ARIMA m
As is known, agriculture is very important in China, but the problem about pests has hampered the further development of Chinese agriculture. digital image-processing technology and mathematical morphology are referre...
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ISBN:
(纸本)9780387772523
As is known, agriculture is very important in China, but the problem about pests has hampered the further development of Chinese agriculture. digital image-processing technology and mathematical morphology are referred to as the main research methods, and tiny pets like aphids among field are referred to as the research objects. imageprocessing technology such as edge-enhancing diffusion filtering, mathematical morphology and watershed segmentation algorithm is used to monitor pest population density, which greatly raises efficiency of pest data acquisition. After the segmentation of the image of the pests, the number of the insect individuals can be obtained from the background by using imageprocessing technology. Computer imageprocessing technology provides a possibility to solve this problem and becomes a very important direction to monitor regional pest population density.
As is known,agriculture is very important in China,but the problem about pests has hampered the further development of Chinese *** image-processing technology and mathematical morphology are referred to as the main re...
详细信息
As is known,agriculture is very important in China,but the problem about pests has hampered the further development of Chinese *** image-processing technology and mathematical morphology are referred to as the main research methods,and tiny pets like aphids among field are referred to as the research *** processing technology such as edgeenhancing diffusion filtering,mathematical morphology and watershed segmentation algorithm is used to monitor pest population density,which greatly raises efficiency of pest data *** the segmentation of the image of the pests,the number of the insect individuals can be obtained from the background by using imageprocessing *** imageprocessing technology provides a possibility to solve this problem and becomes a very important direction to monitor regional pest population density.
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