As an endophytic fungus, the growth-promoting effects of Piriformospora indica have been widely confirmed in many of its host plants. In this study, we investigated the influences of P. indica colonization on the growth of the daughter plants of two strawberry cultivars, ‘Benihoppe’ and ‘Sweet Charlie.’ The results showed that the fungus colonization significantly promoted the growth of the daughter plants of both of the two strawberry varieties. Its colonization greatly improved almost all of the growth parameters of the ‘Benihoppe’ daughter plants, including the above-ground fresh weight, above-ground dry weight, root fresh weight, root dry weight, plant height, petiole length, leaf area, number of roots and chlorophyll content. However, the fungus colonization showed significant improving effects on only the above-ground fresh weight, root fresh weight and root dry weight of ‘Sweet Charlie.’ Surprisingly, the average root length of ‘Benihoppe’ and ‘Sweet Charlie’ was suppressed by about 14.3% and 24.6%, respectively, by P. indica. Moreover, after P. indica colonization, the leaf nitrate reductase activity and root activity upregulated by 30.12% and 12.74%, and 21.85% and 21.16%, respectively, for the ‘Benihoppe’ and ‘Sweet Charlie’ daughter plants. Our study indicated that P. indica could promote the growth of strawberry daughter plants by improving rooting, strengthening photosynthetic pigments production and nutrient absorption and accelerating biomass accumulation. The fungus shows great potential to be used in the strawberry industry, especially in the breeding of daughter plants.

Viruses are factors that can fluctuate insect populations, including honey bees. Most honey bee infecting viruses are single positive-stranded RNA viruses that may not specifically infect honey bees and can be hazardous to other pollinator insects. In addition, these viruses could synergize with other stressors to worsen the honey bee population decline. To identify the underlying detailed mechanisms, reversed genetic studies with infectious cDNA clones of the viruses are necessary. Moreover, an infectious cDNA clone can be applied to studies as an ideal virus isolate that consists of a single virus species with a uniform genotype. However, only a few infectious cDNA clones have been reported in honey bee studies since the first infectious cDNA clone was published four decades ago. This article discusses steps, rationales, and potential issues in bee-infecting RNA virus cloning. In addition, failed experiences of cloning a Deformed wing virus isolate that was phylogenetically identical to Kakugo virus were addressed. We hope the information provided in this article can facilitate further developments of reverse-genetic studies of bee-infecting viruses to clarify the roles of virus diseases in the current pollinator declines.

To enhance mid-low-resolution ship detection, existing methods generally use image super-resolution (SR) as a preprocessing step and feed the super-resolved images to the detectors. However, these methods only use high-resolution (HR) images as ground-truth labels to supervise the training of their SR module but overlook the rich HR information in the detection stage. Inspired by the recent advances in knowledge distillation, in this letter, we design a feature distillation framework to fully exploit the information in ground-truth HR images to handle mid-low-resolution ship detection. Our framework consists of a student network and a teacher network. The student network first super-resolves input images using an SR module and then feeds the super-resolved images to the detection module. The teacher network whose architecture is the same as the student detection module directly takes HR images as input to generate HR feature representation and then distills these HR features to the student network through a distillation loss. Using our feature distillation framework, HR images are not only used as ground-truth labels to train the SR module but also provide "ground-truth" features to train the detection module, which enhances the detection performance of the student network. We apply our framework to several popular detectors, including FCOS, Faster-RCNN, Mask-RCNN, and Cascase-RCNN, and conduct extensive ablation studies to validate its effectiveness and generality. Experimental results on the HRSC2016, DOTA, and NWPU VHR-10 datasets demonstrate that, when applying our framework to Faster-RCNN, our method can outperform several state-of-the-art detection methods in terms of mAP50 and mAP75.

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Taking a transmission system under alternating axial load as an example, this paper builds the shafting model in Romax. By using the orthogonal experimental design method, the influence law of different factor level combinations on bearing performance is analyzed. The simulation results show that the axial assembly preload has a great influence on the contact stress load distribution in the inner raceway, the housing hole design tolerance of transition fit has a second influence, and the shaft design tolerance of interference fit has a smaller influence. The preload design parameters under service conditions are optimized: shaft design tolerance (k6), housing hole design tolerance (K6) and axial assembly preload (30 μm).