83 research outputs found

    Role of Noncoding Regions in Newcastle Disease Virus Replication and pathogenesis

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    The roles of the intergenic sequences (IGS) and untranslated regions (UTR) in Newcastle disease virus (NDV) transcription and pathogenesis are not clear. By our established reverse genetics system, we investigated the role of these noncoding regions in NDV life cycle. The infectious recombinant viruses containing increased/decreased length of F-HN and HN-L IGS were recovered and the transcription and pathogenicity of mutants were characterized. Our studies indicated that increased F-HN or HN-L IGS length reduced the downstream gene transcription. Morever, all IGS mutants were attenuated in chickens and the level of attenuation was increased as the length of IGS increased. The mutant viruses with modified 5' and 3' UTR of HN mRNA were also recovered. The transcription, translation and pathogenecity of these recombinant viruses were characterized. Our studies indicated that the UTRs are not essential for NDV replication in vitro. Complete deletions of 5' HN UTR down regulated its transcription, translation levels and incorporation of HN protein into virus particle, therefore, attenuated the pathogenicity of NDV in chickens. Moreover, studies on the HN UTRs replaced with corresponding NP UTRs virus suggested that UTRs can be exchanged between NDV mRNAs without affecting the replication of virus in vitro and in vivo. In summary, my research identifies for the first time the role of noncoding regions in NDV replication and pathogenesis and provides novel methods for the development of attenuated live vaccines for NDV

    A Correlation Information-based Spatiotemporal Network for Traffic Flow Forecasting

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    The technology of traffic flow forecasting plays an important role in intelligent transportation systems. Based on graph neural networks and attention mechanisms, most previous works utilize the transformer architecture to discover spatiotemporal dependencies and dynamic relationships. However, they have not considered correlation information among spatiotemporal sequences thoroughly. In this paper, based on the maximal information coefficient, we present two elaborate spatiotemporal representations, spatial correlation information (SCorr) and temporal correlation information (TCorr). Using SCorr, we propose a correlation information-based spatiotemporal network (CorrSTN) that includes a dynamic graph neural network component for integrating correlation information into spatial structure effectively and a multi-head attention component for modeling dynamic temporal dependencies accurately. Utilizing TCorr, we explore the correlation pattern among different periodic data to identify the most relevant data, and then design an efficient data selection scheme to further enhance model performance. The experimental results on the highway traffic flow (PEMS07 and PEMS08) and metro crowd flow (HZME inflow and outflow) datasets demonstrate that CorrSTN outperforms the state-of-the-art methods in terms of predictive performance. In particular, on the HZME (outflow) dataset, our model makes significant improvements compared with the ASTGNN model by 12.7%, 14.4% and 27.4% in the metrics of MAE, RMSE and MAPE, respectively.Comment: 19 pages, 13 figures, 5 table

    No-reference image quality assessment based on the AdaBoost BP neural network in the wavelet domain

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    Considering the relatively poor robustness of quality scores for different types of distortion and the lack of mechanism for determining distortion types, a no-reference image quality assessment (NR-IQA) method based on the AdaBoost BP Neural Network in Wavelet domain (WABNN) is proposed. A 36-dimensional image feature vector is constructed by extracting natural scene statistics (NSS) features and local information entropy features of the distorted image wavelet sub-band coefficients in three scales. The ABNN classifier is obtained by learning the relationship between image features and distortion types. The ABNN scorer is obtained by learning the relationship between image features and image quality scores. A series of contrast experiments are carried out in the LIVE database and TID2013 database. Experimental results show the high accuracy of the distinguishing distortion type, the high consistency with subjective scores and the high robustness of the method for distorted images. Experiment results also show the independence for the database and the relatively high operation efficiency of this method

    RNA-seq analysis reveals transcriptome reprogramming and alternative splicing during early response to salt stress in tomato root

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    Salt stress is one of the dominant abiotic stress conditions that cause severe damage to plant growth and, in turn, limiting crop productivity. It is therefore crucial to understand the molecular mechanism underlying plant root responses to high salinity as such knowledge will aid in efforts to develop salt-tolerant crops. Alternative splicing (AS) of precursor RNA is one of the important RNA processing steps that regulate gene expression and proteome diversity, and, consequently, many physiological and biochemical processes in plants, including responses to abiotic stresses like salt stress. In the current study, we utilized high-throughput RNA-sequencing to analyze the changes in the transcriptome and characterize AS landscape during the early response of tomato root to salt stress. Under salt stress conditions, 10,588 genes were found to be differentially expressed, including those involved in hormone signaling transduction, amino acid metabolism, and cell cycle regulation. More than 700 transcription factors (TFs), including members of the MYB, bHLH, and WRKY families, potentially regulated tomato root response to salt stress. AS events were found to be greatly enhanced under salt stress, where exon skipping was the most prevalent event. There were 3709 genes identified as differentially alternatively spliced (DAS), the most prominent of which were serine/threonine protein kinase, pentatricopeptide repeat (PPR)-containing protein, E3 ubiquitin-protein ligase. More than 100 DEGs were implicated in splicing and spliceosome assembly, which may regulate salt-responsive AS events in tomato roots. This study uncovers the stimulation of AS during tomato root response to salt stress and provides a valuable resource of salt-responsive genes for future studies to improve tomato salt tolerance

    Investigation on viscosity and non-isothermal crystallization behavior of P-bearing steelmaking slags with varying TiO2 content

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    The viscous flow and crystallization behavior of CaO-SiO2-MgO-Al2O3-FetO-P2O5-TiO2 steelmaking slags have been investigated over a wide range of temperatures under Ar (High purity, >99.999 pct) atmosphere, and the relationship between viscosity and structure was determined. The results indicated that the viscosity of the slags slightly decreased with increasing TiO2 content. The constructed nonisothermal continuous cooling transformation (CCT) diagrams revealed that the addition of TiO2 lowered the crystallization temperature. This can mainly be ascribed to that addition of TiO2 promotes the formation of [TiO6]-octahedra units and, consequently, the formation of MgFe2O4-Mg2TiO4 solid solution. Moreover, the decreasing viscosity has a significant effect on enhancing the diffusion of ion units, such as Ca2+ and [TiO4]-tetrahedra, from bulk melts to the crystal–melt interface. The crystallization of CaTiO3 and CaSiTiO5 was consequently accelerated, which can improve the phosphorus content in P-enriched phase (n2CaO·SiO2-3CaO·P2O5). Finally, the nonisothermal crystallization kinetics was characterized and the activation energy for the primary crystal growth was derived such that the activation energy increases from −265.93 to −185.41 KJ·mol−1 with the addition of TiO2 content, suggesting that TiO2 lowered the tendency for the slags to crystallize

    Role of Intergenic Sequences in Newcastle Disease Virus RNA Transcription and Pathogenesisâ–¿

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    Newcastle disease virus (NDV), a member of the family Paramyxoviridae, has a nonsegmented negative-sense RNA genome consisting of six genes (3′-NP-P-M-F-HN-L-5′). The first three 3′-end intergenic sequences (IGSs) are single nucleotides (nt), whereas the F-HN and HN-L IGSs are 31 and 47 nt, respectively. To investigate the role of IGS length in NDV transcription and pathogenesis, we recovered viable viruses containing deletions or additions in the IGSs between the F and HN and the HN and L genes. The IGS of F-HN was modified to contain an additional 96 nt or more or a deletion of 30 nt. Similarly, the IGS of HN-L was modified to contain an additional 96 nt or more or a deletion of 42 nt. The level of transcription of each mRNA species (NP, F, HN, and L) was examined by Northern blot analysis. Our results showed that NDV can tolerate an IGS length of at least 365 nt. The extended lengths of IGSs down-regulated the transcription of the downstream gene and suggested that 31 nt in the F-HN IGS and 47 nt in the HN-L IGS are required for efficient transcription of the downstream gene. The effect of IGS length on pathogenicity of mutant viruses was evaluated in embryonated chicken eggs, 1-day-old chicks, and 6-week-old chickens. Our results showed that all IGS mutants were attenuated in chickens. The level of attenuation increased as the length of the IGS increased. Interestingly, decreased IGS length also attenuated the viruses. These findings can have significant applications in NDV vaccine development

    Stable 4×10 Gb/S Mimo-Free Im/Dd Mdm Transmission Enabled By Degenerate-Mode-Selective Couplers

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    We propose and fabricate non-circularly-symmetric degenerate-mode-selective couplers for LP11 and LP21 modes, based on which we demonstrate stable 4-mode MIMO-free MDM transmission over 10-km of weakly-coupled FMF with 10-Gb/s OOK and simple direct detection

    Adaptive Collaborative Gaussian Mixture Probability Hypothesis Density Filter for Multi-Target Tracking

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    In this paper, an adaptive collaborative Gaussian Mixture Probability Hypothesis Density (ACo-GMPHD) filter is proposed for multi-target tracking with automatic track extraction. Based on the evolutionary difference between the persistent targets and the birth targets, the measurements are adaptively partitioned into two parts, persistent and birth measurement sets, for updating the persistent and birth target Probability Hypothesis Density, respectively. Furthermore, the collaboration mechanism of multiple probability hypothesis density (PHDs) is established, where tracks can be automatically extracted. Simulation results reveal that the proposed filter yields considerable computational savings in processing requirements and significant improvement in tracking accuracy
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