Genome-wide analysis of the CCCH zinc finger family in longan:Characteristic identification and expression profiles in Dimocarpus longan Lour

CCCH(C3 H) Zinc finger(Znf) transcription factors(TFs), as a novel type of Znf gene, regulate the expression of genes by binding to their mRNAs and play important roles in plant growth and development and abiotic stress resistance.Longan(Dimocarpous longan) is a tropical/subtropical fruit tree of great economic importance in Southeast Asia.However, genomic information on C3 H and their functions in longan are still unknown. In this study, a comprehensive analysis of the longan C3 H(DlC3 H) gene family was carried out. A total of 49 DlC3 H genes in three clades were identified from the longan genome database. Characteristics of the genes were analyzed with respect to gene structure,motif composition, phylogenetic tree and potential functions. The analysis of alternative splicing(AS) events suggested that AS events in DlC3 H genes were related to the transformation from longan non-embryonic to embryonic cultures.Promoter analysis indicated that most of the DlC3 H genes included cis-acting elements associated with hormones and stresses responses. Quantitative real-time PCR(qRT-PCR) analysis indicated that 26 of the 49 DlC3 Hs, which possess methyl jasmonate(MeJA) and abscisic acid(ABA) responsive cis-acting elements, showed differential expression patterns under treatment with ABA, MeJA and their endogenous inhibitors, suggesting that DlC3 Hs might be involved in the ABA and MeJA signaling pathways. The expression profiles of 17 of the 49 DlC3 Hs in non-embryonic callus and three tissues of embryonic cultures showed that only five of the 17 DlC3 Hs had the same expression trends as the FPKM trends in transcriptome data;the expression levels of DlC3 H07/14/16/36/49 in embryogenic callus and DlC3 H04/38 in globular embryos were high, suggesting that they have different functions in embryonic development. Further, we verified that DlC3 H01/03/05/11/19/39 were regulated by sRNAs by a modified 5’ RLM-RACE method. This study provides the first systematic analysis of C3 H genes in longan, and found that C3 H genes may be involved in hormone and stress responses, and somatic embryogenesis. Our preliminary investigation may provide clues to further studies on the characteristics and functions of this family in longan.

Modeling and identification for soft sensor systems based on the separation of multi-dynamic and static characteristics

Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.

Quarantine Identification of Dendroctonus punctatus

Dendroctonus spp. is one of the most portable pests in imported and ex- ported timber and wooden packages, and it is an important object of the port quarantine. Making rapid and accurate identification of Dendroctonus spp. is an im- portant method to reduce the invasion risk of Dendroctonus spp. for China. In this paper, Dendroctonus punctatus, which belongs to the Dendroctonus spp., is intro- duced in detail from the aspects of taxonomic status, biological characteristics, mor- phological characteristics and the invasion risk, providing reference for the identifica- tion of Dendroctonus punctatus in inspection and quarantine.

Nonlinear Systems Identification via an Input-Output Model Based on a Feedforward Neural Network

This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.

Indication to distinguish the burst region of coal gas from seismic data

The velocity of an over-burst coal seam based on laboratory test results. This seam is about 1/3 compared to a normal coal can be considered as a basis to confirm the area of coal and gas burst by seismic exploration technique. Similarly, the simulation result of the theoretical seismic model shows that there is obvious distinction between over-burst coal and normal coal based on the coal reflection＇s travel-time, energy and frequency. The results from the actual seismic data acquired in the coal and gas over-burst cases is consistent with that of the laboratory and seismic modeling; that is, in the coal and gas burst region, seismic reflection travel time is delayed, seismic amplitude is weakened and seismic frequency is reduced. Therefore, it can be concluded that seismic exploration tech- nique is promising for use in distinguishing coal and gas over-burst regions based on the variation of seismic reflection travel time, amplitude and frequency.

Quantifying the characteristics of particulate matters captured by urban plants using an automatic approach

It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope（SEM）micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found（1） Rosa xanthina Lindl（shrub species） had greater retention efficiency than Broussonetia papyrifera（broadleaf species） and Pinus bungeana Zucc.（coniferous species）, in terms of particle number and particle area cover.（2） 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.（3） 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.