| 1 | Preferential feeding of an anthocorid predator Blaptostethus pallescens Poppius on different stages of cotton mealybug显示文摘Blaptostethus pallescens Poppius (Heteroptera:Anthocoridae),which is amenable to mass rearing,has proved to be a potential predator of sucking pests like mites and thrips.Recently,the cotton mealybug Phenacoccus solenopsis Tinsley emerged as a serious pest on cotton in India.Laboratory studies indicated that B.pallescens could feed on the cotton mealybug.Hence,further investigations were conducted to understand the stage of the predator which is most potential and the pest stage preferred by the predator.Mature nymphs and adults of B.pallescens could predate equally well on the neonates of cotton mealybug.Young (three to four-day-old) nymphs of the predator could not feed on any stage of the cotton mealybug.Mature nymphs (seven-day-old and above) and adults could effectively predate on both young and mature cotton mealybug crawlers,though preference was more for the younger crawlers.However,nymphs and adults of B.pallescens could not predate on the adult stage of the mealybug.Different predator:pest ratios were tested in cage studies and it emerged that B.pallescens adults released against the mealybug crawlers at a ratio of 1:5 and nymphal release at 1:10 caused maximum mortality of the mealybug crawlers.Considering the fast multiplication rate of cotton mealybug and the large number of predators which have to be released to manage them,further detailed studies are necessary on utilizing B.pallescens to target the neonates and younger stages of the cotton mealybug in field conditions. | Gupta Tripti | 2011 | 环境昆虫学报2011，33，4： | 0 |
| 2 | Robust Magnification Independent Colon Biopsy Grading System over Multiple Data Sources显示文摘Automated grading of colon biopsy images across all magnifications is challenging because of tailored segmentation and dependent features on each magnification.This work presents a novel approach of robust magnification-independent colon cancer grading framework to distinguish colon biopsy images into four classes:normal,well,moderate,and poor.The contribution of this research is to develop a magnification invariant hybrid feature set comprising cartoon feature,Gabor wavelet,wavelet moments,HSV histogram,color auto-correlogram,color moments,and morphological features that can be used to characterize different grades.Besides,the classifier is modeled as a multiclass structure with six binary class Bayesian optimized random forest(BO-RF)classifiers.This study uses four datasets(two collected from Indian hospitals—Ishita Pathology Center(IPC)of 4X,10X,and 40X and Aster Medcity(AMC)of 10X,20X,and 40X—two benchmark datasets—gland segmentation(GlaS)of 20X and IMEDIATREAT of 10X)comprising multiple microscope magnifications.Experimental results demonstrate that the proposed method outperforms the other methods used for colon cancer grading in terms of accuracy(97.25%-IPC,94.40%-AMC,97.58%-GlaS,99.16%-Imediatreat),sensitivity(0.9725-IPC,0.9440-AMC,0.9807-GlaS,0.9923-Imediatreat),specificity(0.9908-IPC,0.9813-AMC,0.9907-GlaS,0.9971-Imediatreat)and F-score(0.9725-IPC,0.9441-AMC,0.9780-GlaS,0.9923-Imediatreat).The generalizability of the model to any magnified input image is validated by training in one dataset and testing in another dataset,highlighting strong concordance in multiclass classification and evidencing its effective use in the first level of automatic biopsy grading and second opinion. | Tina Babu Deepa Gupta Tripty Singh Shahin Hameed Mohammed Zakariah Yousef Ajami Alotaibi | 2021 | Computers, Materials & Continua2021，，10： | 0 |
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