The relationships between plant viruses, their herbivore vectors and host plants can be beneficial, neutral, or antagonistic, depending on the species involved. This variation in relationships may affect the process of biological invasion and the displacement of indigenous species by invaders when the invasive and indigenous organisms occur with niche overlap but differ in the interactions. The notorious invasive B biotype of the whitefly complex Bemisia tabaci entered China in the late 1990s and is now the predominant or only biotype in many regions of the country. Tobacco curly shoot virus (TbCSV) and Tomato yellow leaf curl China virus (TYLCCNV) are two whitefly-transmitted begomoviruses that have become widespread recently in south China. We compared the performance of the invasive B and indigenous ZHJ1 whitefly biotypes on healthy, TbCSV-infected and TYLCCNV-infected tobacco plants. Compared to its performance on healthy plants, the invasive B biotype increased its fecundity and longevity by 12 and 6 fold when feeding on TbCSV-infected plants, and by 18 and 7 fold when feeding on TYLCCNV-infected plants. Population density of the B biotype on TbCSV- and TYLCCNV-infected plants reached 2 and 13 times that on healthy plants respectively in 56 days. In contrast, the indigenous ZHJ1 performed similarly on healthy and virus-infected plants. Virus-infection status of the whiteflies per se of both biotypes showed limited effects on performance of vectors on cotton, a nonhost plant of the viruses. The indirect mutualism between the B biotype whitefly and these viruses via their host plants, and the apparent lack of such mutualism for the indigenous whitefly, may contribute to the ability of the B whitefly biotype to invade, the displacement of indigenous whiteflies, and the disease pandemics of the viruses associated with this vector.

In this paper, we present a large-scale dataset and establish a baseline for prohibited item discovery in Security Inspection X-ray images. Our dataset, named SIXray, consists of 1,059,231 X-ray images, in which 6 classes of 8,929 prohibited items are manually annotated. It raises a brand new challenge of overlapping image data, meanwhile shares the same properties with existing datasets, including complex yet meaningless contexts and class imbalance.

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Certain biotypes of the Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) complex cause extensive damage and are important pests and virus vectors in agricultural crops throughout the world. Among the most invasive and well studied are the B and Q biotypes. Recent reports in Shandong Province, China, have indicated that the Q biotype was introduced there in approximately 2005, whereas the B biotype has been established there for approximately 10 yr. Even so, the present distribution of the two biotypes in Shandong has not been examined. The results of this study showed that the B and Q biotypes are both present in Shandong Province based on bar-coding using a approximately 450-base fragment of the mitochondrial cytochrome oxidase I (mtCOI) gene. In addition, a B biotype-specific polymerase chain reaction primer pair that amplifies a approximately 300 bp mtCOI fragment was designed and used to examine the biotype composition of B. tabaci in selected crops from six provincial locations, using the general mtCOI primers as an internal positive control for DNA quality. The results of this study indicated that the Q biotype was the predominant B. tabaci colonizing all of the crops in the study sites examined. This suggests that the Q biotype has displaced the B biotype in Shandong Province of China, which until now was the predominant biotype. This is the first report of the displacement of the B by the Q biotype in field grown crops in China, and in a locale where neither the B nor the Q biotype is native. We hypothesize that this phenomenon may have been exacerbated by the widespread use of neonicotinoid insecticides for whitefly control, given the sustained efficacy thus far of neonicotinoids against the B biotype, and their failure at times to effectively control the Q biotype.

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Weakly supervised object localization (WSOL) is a challenging problem when given image category labels but requires to learn object localization models. Optimizing a convolutional neural network (CNN) for classification tends to activate local discriminative regions while ignoring complete object extent, causing the partial activation issue. In this paper, we argue that partial activation is caused by the intrinsic characteristics of CNN, where the convolution operations produce local receptive fields and experience difficulty to capture long-range feature dependency among pixels. We introduce the token semantic coupled attention map (TS-CAM) to take full advantage of the self-attention mechanism in visual transformer for long-range dependency extraction. TS-CAM first splits an image into a sequence of patch tokens for spatial embedding, which produce attention maps of long-range visual dependency to avoid partial activation. TS-CAM then re-allocates category-related semantics for patch tokens, enabling each of them to be aware of object categories. TS-CAM finally couples the patch tokens with the semantic-agnostic attention map to achieve semanticaware localization. Experiments on the ILSVRC/CUB-200-2011 datasets show that TS-CAM outperforms its CNN-CAM counterparts by 7.1%/27.1% for WSOL, achieving state-ofthe-art performance.