Interdecadal variability in ecosystem health of Changjiang (Yangtze) River estuary using estuarine biotic integrity index

Ichthyoplankton samples were collected from Changjiang(Yangtze)River estuary in May 2016.Species composition was studied by DNA barcoding and morphological identification.To make better use of the estuarine biotic integrity index(EBI)to assess the ecosystem health of the Changjiang River estuary over the past 30 years,we collected the data of a spring ichthyoplankton survey in the estuary from 1986 to 2016.The EBI was calculated using 12 evaluation metrics,namely,the number of total ichthyoplankton species,estuarine spawning species,estuarine nursery species,estuarine resident species,benthic species,pelagic species,and intolerant species,and the percentages of tolerant species,omnivores,insectivores,carnivores,and natural hybrid species.EBI was calculated in spring in four periods(1986,1999,2007,and 2016)by assigning points of 1,3 or 5,giving values of 50,38,36,and 32,respectively,corresponding to“Good”,“Fair-Poor”,“Fair-Poor”,and“Poor”EBI levels,respectively.Changes in species composition were the primary reason for the significant decreases in EBI between 1986 and 1999,and for the large differences between 1986 and 2007 and between 2007 and 2016.The changes in species composition were influenced by declines in ichthyoplankton species,pollution sensitive species,estuarine nursery species and estuarine sedentary species,and an increase in pollution resistant species.An analysis of EBI interdecadal variability showed that the health status of the Changjiang River estuary ecosystem over the last 30 years first declined and then stabilized at a lower level.This result further settled the argument for urgent protection and restoration of the Changjiang River estuary.

Nonparaxial propagation of radially polarized chirped Airy beams in uniaxial crystal orthogonal to the optical axis

The nonparaxial propagation of radially polarized chirped Airy beams(RPCAiBs) in uniaxial crystal orthogonal to the optical axis is analytically studied. The effects of the first and the second order chirp factors, and the ratio of the extraordinary refractive index to the ordinary refractive index on the nonparaxial evolution of RPCAi Bs in different observation planes are investigated in detail. The results show that when one parameter changes, different components behave differently, and even the same component has various behavior in different directions. The initial slope of RPCAi Bs in the x-direction varies more with the first order chirp factor than that in the y-direction. Meanwhile, with the second order chirp factor becoming larger, the depth of the focus of the y-component in the x-direction decreases while that in the y-direction has no difference. In addition, the different ratios of the extraordinary refractive index to the ordinary refractive index change the difference of the depth of the focus between the x-and the y-components.

A vision system based on CNN-LSTM for robotic citrus sorting Author links open overlay panel

Compared with manual sorting of citrus fruit,vision-based sorting solutions can help achieve higher accuracy and efficiency.In this study,we present a vision system based on CNN-LSTM,which can cooperate with robotic grippers for real-time sorting and is readily applicable to various citrus processing plants.A CNN-based detector was adopted to detect the defective oranges in view and temporarily classify them into corresponding types,and an LSTM-based predictor was used to predict the position of the oranges in a future frame based on image sequential data.The fusion of CNN and LSTM networks enabled the system to track defective ones during rotation and identify their true types,and their future path was also predicted which is vital for predictive control of visually guided robotic grasping.High detection accuracy of 94.1%was obtained based on experimental results,and the error for path prediction was within 4.33 pixels 40 frames later.The average time to process a frame was between 28 and 62 frames per second,which also satisfied real-time performance.The results proved the potential of the proposed system for automated citrus sorting with good precision and efficiency,and it can be readily extended to other fruit crops featuring high versatility.

Tet methylcytosine dioxygenase 2(TET2)deficiency elicits EGFR-TKI(tyrosine kinase inhibitors)resistance in non-small cell lung cancer

Despite epidermal growth factor receptor(EGFR)tyrosine kinase inhibitors(TKl)have shown remarkable efficacy in patients with EGFR-mutant non-small cell lung cancer(NSCLC),acquired resistance inevitably develops,limiting clinical efficacy.We found that TET2 was poly-ubiquitinated by E3 ligase CUL7^(FBXW11) and degraded in EGFR-TKI resistant NSCLC ells.Genetic perturbationof TET2 rendered parental cells more tolerant to TKI treatment.TET2 was stabilized by MEK1 phosphorylation at Ser 1107,while MEK1 inactivation promoted its proteasome degradation by enhancing the recruitment of CUL7^(FBXW11),Loss of TET2 resulted in the upregulation of TNF/NF-kB signaling that confers the EGFR-TKI resistance.Genetic or pharmacological inhibition of NF-kB attenuate the TKI resistance both in vitro and in vivo.Our findings exemplified how a cell growth controlling kinase MEK1 leveraged the epigenetic homeostasis by regulating TET2,and demonstrated an alternative path of non-mutational acquired EGFR-TKI resistance modulated by TET2 deficiency.Therefore,combined strategy exploiting EGFR-TKI and inhibitors of TET2/NF-κB axis holds therapeutic potential for treating NSCLC patients who suffered from this resistance.

Wave Propagation in Viscoelastic Functionally Graded Nanoplates:Comparison of the Integral and Differential Nonlocal Models

As one of the popular non-classical continuum theories in functionally graded material(FGM)nanostructures,the modified nonlocal theory(MNT)has been applied in various mechanical problems.However,due to the difficult solution process,the original integral formulation of MNT(IMNT)is transformed into a differential formulation of MNT(DMNT),which results in an inevitable approximation error.To clarify the consistency and difference between two formulations,the Lamb wave characteristics in viscoelastic FGM nanoplates are investigated.Two mathematical models are established based on the IMNT and DMNT,and solved by the proposed displacement-based and strain-based Legendre polynomial series approaches(LPSAs),respectively.Comparisons with the available data verify the validates of the presented LPSAs.Numerical examples indicate that the results from the DMNT and IMNT are significantly different at high frequencies.Several important differences are discovered.For example,the escape frequency only appears in the results from DMNT,but not in IMNT.In addition to comparing with classical structures,more attention should be paid to the attenuation characteristics of nonlocal nanostructures.

Predicting and Visualizing Citrus Color Transformation Using a Deep Mask-Guided Generative Network

Citrus rind color is a good indicator of fruit development,and methods to monitor and predict color transformation therefore help the decisions of crop management practices and harvest schedules.This work presents the complete workflow to predict and visualize citrus color transformation in the orchard featuring high accuracy and fidelity.A total of 107 sample Navel oranges were observed during the color transformation period,resulting in a dataset containing 7,535 citrus images.A framework is proposed that integrates visual saliency into deep learning,and it consists of a segmentation network,a deep mask-guided generative network,and a loss network with manually designed loss functions.Moreover,the fusion of image features and temporal information enables one single model to predict the rind color at different time intervals,thus effectively shrinking the number of model parameters.The semantic segmentation network of the framework achieves the mean intersection over a union score of 0.9694,and the generative network obtains a peak signal-to-noise ratio of 30.01 and a mean local style loss score of 2.710,which indicate both high quality and similarity of the generated images and are also consistent with human perception.To ease the applications in the real world,the model is ported to an Android-based application for mobile devices.The methods can be readily expanded to other fruit crops with a color transformation period.The dataset and the source code are publicly available at GitHub.