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Abstract Background Orychophragmus violaceus is a potentially important industrial oilseed crop due to the two 24-carbon dihydroxy fatty acids (diOH-FA) that was newly identified from its seed oil via a ‘discontinuous elongation’ process. Although many research efforts have focused on the diOH-FA biosynthesis mechanism and identified the potential co-expressed diacylglycerol acyltranferase (DGAT) gene associated with triacylglycerol (TAG)-polyestolides biosynthesis, the dynamics of metabolic changes during seed development of O. violaceus as well as its associated regulatory network changes are poorly understood. Results In this study, by combining metabolome and transcriptome analysis, we identified that 1,003 metabolites and 22,479 genes were active across four stages of seed development, which were further divided into three main clusters based on the patterns of metabolite accumulation and/or gene expression. Among which, cluster2 was mostly related to diOH-FA biosynthesis pathway. We thus further constructed transcription factor (TF)-structural genes regulatory map for the genes associated with the flavonoids, fatty acids and diOH-FA biosynthesis pathway in this cluster. In particular, several TF families such as bHLH, B3, HD-ZIP, MYB were found to potentially regulate the metabolism associated with the diOH-FA pathway. Among which, multiple candidate TFs with promising potential for increasing the diOH-FA content were identified, and we further traced the evolutionary history of these key genes among species of Brassicaceae. Conclusion Taken together, our study provides new insight into the gene resources and potential relevant regulatory mechanisms of diOH-FA biosynthesis uniquely in seeds of O. violaceus, which will help to promote the downstream breeding efforts of this potential oilseed crop and advance the bio-lubricant industry.

Abstract Currently, high-yield gas reservoirs have been discovered by exploring Lower Paleozoic tight carbonate oil and gas reservoirs in the Changqing area. These reservoirs, however, are impacted by subsequent karstification and diagenesis processes, leading to the formation of complex pore spaces with varying pore diameters ranging from microns to millimeters. Conventional well curves, with a resolution at the decimeter level, can only provide an overview of the reservoir porosity, making it challenging to evaluate the pore structure. On the other hand, electrical imaging logging data has a sampling interval of 0.1 inches and a resolution as fine as 5 mm, providing valuable information for pore structure evaluation in tight reservoirs. Since formation resistivity is influenced by factors like porosity, mud filtrate resistivity, and cementation, the cementation index serves as a reflection of the pore structure. Therefore, by calibrating the cementation index using data obtained from experiments at different scales, the pore structure parameters of tight carbonate reservoirs can be evaluated. This study conducted a comparison between numerous core experiments at various scales and both conventional and imaging log data. A method was proposed for extracting pore size distribution characteristics and calculating the pore size spectrum based on electrical imaging logging, ultimately leading to the establishment of a quantitative evaluation model for the pore structure of tight carbonate reservoirs. The results demonstrated improved accuracy and consistency in interpretation, as confirmed by well test data.

This paper focus on a dynamic event-triggered mechanism to solve fixed-time containment control problems for nonlinear multi-agent systems (MASs) with uncertain disturbances over directed graphs. An event-triggered algorithm based on dynamic variables is proposed to achieve the fixed-time containment control of MASs, which can effectively reduce the number of event-triggered instants. By modifying the auxiliary variables and reconstructing the dynamic variables, the effect of input time-delays in MASs is successfully eliminated. It is noteworthy that only the auxiliary variables are modified while the structure of the dynamic variables is not changed, which further indicates that the designed dynamic event-triggered algorithm is also suitable for solving multi-agent systems with input time-delays. In addition, the setting time associated with the time-delays is also computed and the Zeno behavior is successfully avoided by computing the minimum time interval between event triggering as non-negative. Finally, simulation results are given to verify the effectiveness of proposed control protocol.

The exploration and comprehensive assessment of fractured-vuggy reservoir information have perennially constituted focal points and challenges within the domain of oil and gas reservoir evaluation. The verification of geological phenomena, identification of various fracture and hole types, and the quantitative characterization thereof currently present pressing challenges. This study meticulously examines the deep carbonate reservoirs within the Dengying Formation in the Penglai gas region of the Sichuan Basin. The Core Rolling Scan images reveal five discernible features: unfilled holes, filled holes, filled fractures, open fractures, and algae. The analysis pinpoints three primary challenges in semantic segmentation recognition: the amalgamation of feature scales, class imbalance, and the scarcity of datasets with substantial sample sizes. To address these challenges, this paper introduces a Multi-Scale Feature Aggregation Pyramid Network model (MFAPNet), achieving a pixel accuracy of 68.04% in recognizing the aforementioned five types. Lastly, the model is employed in calculating core porosity, exposing a scaling relationship between wellbore image porosity and core porosity ranging from 1.5 to 3 times. To a certain extent, it reveals the correlation between the wellbore image logging data and the actual formation of the Dengying Formation in the Penglai Gas Field of the Sichuan Basin, and also provides a basis for the subsequent logging evaluation of the formation. The partial code and CHA355 dataset are publicly available at https://github.com/zyng886/MFAPNet.

There is a close dynamic coupling relationship between tectonic and mineralization. Long-term research and observation have found that the formation and location of sandstone-type uranium deposits are obviously controlled by the formation of target layer and the subsequent tectonic uplift and denudation events. In order to describe the formation mechanism and process of different types and horizons of uranium deposits in detail and more reasonably, realize the transformation from theoretical model to prospecting model, and establish a new method and approach for target prediction that can be easily applied, a series of studies has been carried out on the uranium deposits (points) around the Kalamari Mountain in the eastern part of Junggar Basin. The study adopts the methods of the basin structural framework division, the research on burial and denudation history and the apatite fission track simulation in the source area. It is found that different types of uranium deposits (spots) in the periphery of the Kalamari Mountain are different products of the same metallogenic system, namely, uplift and denudation evolution. The basin subsidence curve and apatite fission track simulation in the source area show that the eastern Junggar basin has experienced 160−140, 90−70 Ma and about 20 Ma three rapid uplift and denudation stages since the Middle and Late Jurassic. These tectonic events have induced obvious uranium mineralization. The scale and stage of uranium mineralization are controlled strictly by the intensity and stage of tectonic uplift and denudation. In the process of uranium mineralization, tectonic development and evolution play a leading role. Large-scale uranium mineralization is mainly developed in the structural slope zone with a complete mineralization system. For example, the Kamusite progradation (denudation) multi-period same-direction superposition and the Beisantai retrogradation far source uranium mineralization model can often form some large-scale deposits. In general, a large-scale uranium mineralization will not develop in the sections with complex and variable structural forms, such as the piedmont area at the southern edge of the Kalamari Mountain. The summary of the above regional tectonic uplift, uranium mineralization sequence and ore-control combination provide a scientific basis for the prediction of uranium mineralization prospect in this area, and can be applied to the prospecting of sandstone-type uranium deposits in other basins.

Abstract Background The genus Sanicula comprises ca. 45 taxa, widely distributed from East Asia to North America, which is a taxonomically difficult genus with high medicinal value in Apiaceae. The systematic classification of the genus has been controversial for a long time due to varied characters in key morphological traits. China is one of the most important distributed centers, with ca. 18 species and two varieties. At present, chloroplast genomes are generally considered to be conservative and play an important role in evolutionary relationship study. To investigate the plastome evolution and phylogenetic relationships of Chinese Sanicula, we comprehensively analyzed the structural characteristics of 13 Chinese Sanicula chloroplasts and reconstructed their phylogenetic relationships. Results In present study, four newly complete chloroplast genome of Sanicula taxa by using Illumina sequencing were reported, with the typical quadripartite structure and 155,396–155,757 bp in size. They encoded 126 genes, including 86 protein-coding genes, 32 tRNA genes and 8 rRNA genes. Genome structure, distributions of SDRs and SSRs, gene content, among Sanicula taxa, were similar. The nineteen intergenic spacers regions, including atpH-atpI, ndhC-trnM, petB-petD, petD-rpoA, petN-psbM, psaJ-rpl33, rbcL-accD, rpoB-trnC, rps16-trnQ, trnE-psbD, trnF-ndhJ, trnH-psbA, trnN-ndhF, trnS-psbZ, trnS-trnR, trnT-trnF, trnV-rps12, ycf3-trnS and ycf4-cemA, and one coding region (ycf1 gene) were the most variable. Results of maximum likelihood analysis based on 79 unique coding genes of 13 Chinese Sanicula samples and two Eryngium (Apiaceae-Saniculoideae) species as outgroup taxa revealed that they divided into four subclades belonged to two clades, and one subclade was consistent with previously traditional Sanicula section of its system. The current classification based on morphology at sect. Sanicla and Sect. Tuberculatae in Chinese Sanicula was not supported by analysis of cp genome phylogeny. Conclusions The chloroplast genome structure of Sanicula was similar to other angiosperms and possessed the typical quadripartite structure with the conserved genome arrangement and gene features. However, their size varied owing to expansion/contraction of IR/SC boundaries. The variation of non-coding regions was larger than coding regions of the chloroplast genome. Phylogenetic analysis within these Chinese Sanicula were determined using the 79 unique coding genes. These results could provide important data for systematic, phylogenomic and evolutionary research in the genus for the future studies.

The severity of rice blast and its impacts on rice yield are closely related to the inoculum quantity of Magnaporthe oryzae, and automatic detection of the pathogen spores in microscopic images can provide a rapid and effective way to quantify pathogen inoculum. Traditional spore detection methods mostly rely on manual feature extraction and shallow machine learning models, and are mostly designed for the indoor counting of a single spore class, which cannot handle the interference of impurity particles in the field. This study achieved automatic detection of rice blast fungus spores in the mixture with other fungal spores and rice pollens commonly encountered under field conditions by using deep learning based object detection techniques. First, 8959 microscopic images of a single spore class and 1450 microscopic images of mixed spore classes, including the rice blast fungus spores and four common impurity particles, were collected and labelled to form the benchmark dataset. Then, Faster R-CNN, Cascade R-CNN and YOLOv3 were used as the main detection frameworks, and multiple convolutional neural networks were used as the backbone networks in training of nine object detection algorithms. The results showed that the detection performance of YOLOv3_DarkNet53 is superior to the other eight algorithms, and achieved 98.0% mean average precision (intersection over union > 0.5) and an average speed of 36.4 frames per second. This study demonstrated the enormous application potential of deep object detection algorithms in automatic detection and quantification of rice blast fungus spores.

It is difficult to identify the fluid properties with one single logging curve in a caved-fracture reservoir due to multi-stage tectonism, diagenetic evolution, rapid lithology change, developed fractures, and significant heterogeneity. Therefore, a stack generalization-based method is proposed for improving fluid identification accuracy. First, a traditional method with cross-plots is adopted by coring and logging data, but it is found that the identification effect of the caved-fracture reservoir fluid is poor. Second, based on the cross-plot, a correlation analysis is conducted to select sensitive logging parameters such as resistivity, compensated neutron, density, acoustic, and total hydrocarbon, which reflect changes in fluid properties, as feature vectors for the identification of fluid types in caved-fracture reservoirs. Third, support vector machine, k-nearest neighbor algorithm, decision tree, and stochastic gradient descent classification are selected as the base learners. 80% of the data sample points and the remaining 20% are selected as training and test samples for building the stacking models to verify the prediction accuracy of the model. Finally, a fully connected neural network is used as a meta-learner to control the final output. The experimental results show that the prediction accuracy of the stack generalization method can reach 88%. Compared with the cross-plot and single machine learning discriminant model, the fluid identification method based on the stack generalization model has a better effect and can improve the fluid identification effect of caved-fracture reservoirs in the study area.

The lacustrine shale, represented by the Lianggaoshan Formation, is widely distributed in oil and gas basins of China and will be a key target for unconventional hydrocarbon exploration in the future. Due to the complexity of geological conditions, the distribution of lacustrine shale and the mechanism of organic matter (OM) enrichment show significant differences between different basins. In this study, seismic interpretation, core observation, high-frequency geochemical analysis and other methods are integrated to reveal factors controlling lacustrine shale distribution and OM accumulation in lacustrine shale. The results suggest that six bottom-to-top organic-rich shale intervals are identified within the Lianggaoshan Formation due to lake-basin migration. The migration process of depocenters controls the planar distribution of lacustrine organic-rich shale. The organic-rich lacustrine shale within 1st Member and 2nd Member is characterized by relatively high paleoproductivity and dysoxic condition. The lacustrine organic-rich shale of the upper to the top of 3rd Member is characterized by relatively low paleoproductivity, relatively high terrestrial input, and dysoxic condition. Paleoproductivity and preservation condition caused by lake-level rise are generally the major influencing factor of organic matter accumulation in 1st Member and 2nd Member organic-rich shale. The input of terrestrial OM, and the condition of preservation caused by rapid deposition are the major factors controlling OM accumulation in 3rd Member of Lianggaoshan Formation.

Assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation strategies. Sang et al. assemble a reference genome for Populus koreana and combine population genomics and modelling to predict spatiotemporal responses to climate change.

The three-dimensional trajectory tracking of AUV is an important basis for it to complete its task. Due to many uncertain disturbances such as wind, wave and current on the sea, it is easy to cause problems such as slow convergence speed of the controller and saturation of the controller output in the three-dimensional trajectory tracking control of AUV. And the dynamic uncertainty of AUV's own model will have a great negative impact on AUV's trajectory tracking control. In order to solve the problem of slow convergence speed of the above controller, the finite time control method is introduced into the designed position controller. In order to solve the problem of AUV controller output saturation, an auxiliary dynamic system is designed to compensate the system control output saturation. In order to solve the uncertainty of AUV model, a reduced order extended observer is designed in the dynamic controller. It can observe the motion parameters of AUV at any time, and compensate the uncertainty of model uncertainty and external environment disturbance in real time. The control method in this paper is simulated in a three-dimensional model. The experimental results show that the convergence speed, control accuracy, robustness and tracking effect of AUV are higher than those of common trajectory tracker. The algorithm is loaded into the "sea exploration Ⅱ" AUV and verified by experiments in Suzhou lake. The effect of AUV navigation basically meets the task requirements, in which the mean value of pitch angle and heading angle error is less than 8 degrees and the mean value of depth error is less than 0.1M. The trajectory tracker can better meet the trajectory tracking control needs of the AUV.

The Jurassic Lianggaoshan Formation lacustrine shale oil is the most potential exploration target of unconventional hydrocarbon resource in Southwest China. In this study, nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), low-temperature N2 adsorption (LTNA), and high pressure mercury intrusion mercury injection capillary pressure are intergrated to reveal pore structure and its controlling factors of Lianggaoshan Formation lacustrine shale reservoir. Results indicate that three types of lithology combination are classified in the Jurassic Liangggaoshan lacustrine shale reservoir. Type A comprises pure shale. Type B is characterized by frequent shell limestone interbedding. Type C is characterized by frequent siltstone interbedding. The Type C shale is characterized by relatively high proportion of organic pores, high development and good connectivity of nanopores, and highest pore volume and Surface area. The nanopores of Lianggaoshan lacustrine shales are mainly dominated by mesopores and part of the macropores. Among them, the PV and SA are both mainly dominated by micropores. The enrichment of organic matter has little effect on the development of micropores, and does not affect the mesopore and macropore development. Quartz particles in Lianggaoshan lacustrine shale do not clearly facilitate the development of micropore and mesopore-macropore. Intraparticle pore in feldspar clast is an important component of mesopore and macropore. Clay minerals has no positive effect on the formation of micropore and mesopore-macropore.

Chaotic systems and signals are used in a variety of technical and technical applications due to their wide range of noise-like performance and random behaviour. In this study to diversify potential chaotic signal generator circuits; Lu-Chen 2003 system with multi-scroll attractors was first designed an electronic oscillator circuit in a computer environment and then a real electronic circuit was manufactured. The presented results of the comparison simulation and the oscilloscope show that a successful design has been achieved.

This paper reports the method for constructing multiple coexisting attractors from a chaotic system. First, a new four-dimensional chaotic system with only one equilibrium and two coexisting strange attractors is established. By using bifurcation diagrams and Lyapunov exponents, the dynamical evolution of the new system is presented. Second, a feasible and effective method is applied to construct an infinite number of coexisting attractors from the new system. The core of this method is to batch replicate the attractor of the system in phase space via generating multiple invariant sets and the generation of invariant sets depends on the equilibria, which can be extended by using some simple functions with multiple zeros. Finally, we give some numerical results of the appearance of multiple coexisting attractors in the system with sine and sign functions for demonstrating the effectiveness of the method.

This paper proposes a new no-equilibrium chaotic system that has the ability to yield infinitely many coexisting hidden attractors. Dynamic behaviors of the system with respect to the parameters and initial conditions are numerically studied. It shows that the system has chaotic, quasiperiodic, and periodic motions for different parameters and coexists with a large number of hidden attractors for different initial conditions. The circuit and microcontroller implementations of the system are given for illustrating its physical meaning. Also, the synchronization conditions of the system are established based on the adaptive control method.

This paper is concerned with the consensus problem for second-order multiagent systems (MASs) with directed signed networks and local communication delays. First, under a strongly connected directed graph, some properties for signed digraph and the model of second-order MASs are provided. A distributed nonlinear consensus control protocol is proposed for implementing consensus of second-order MASs with signed digraph and communication delay. Then, for structurally balanced and unbalanced networks, the consensus of second-order MASs with directed signed networks and local delays is proved via the Lyapunov method and Barbalat lemma. Simulation examples are given to demonstrate the effectiveness of our results.

Cycadales is an extant group of seed plants occurring in subtropical and tropical regions comprising putatively three families and 10 genera. At least one complete plastid genome sequence has been reported for all of the 10 genera except Microcycas, making it an ideal plant group to conduct comprehensive plastome comparisons at the genus level. This article reports for the first time the plastid genome of Microcycas calocoma. The plastid genome has a length of 165,688 bp with 134 annotated genes including 86 protein-coding genes, 47 non-coding RNA genes (39 tRNA and eight rRNA) and one pseudogene. Using global sequence variation analysis, the results showed that all cycad genomes share highly similar genomic profiles indicating significant slow evolution and little variation. However, identity matrices coinciding with the inverted repeat regions showed fewer similarities indicating that higher polymorphic events occur at those sites. Conserved non-coding regions also appear to be more divergent whereas variations in the exons were less discernible indicating that the latter comprises more conserved sequences. Phylogenetic analysis using 81 concatenated protein-coding genes of chloroplast (cp) genomes, obtained using maximum likelihood and Bayesian inference with high support values (>70% ML and = 1.0 BPP), confirms that Microcycas is closest to Zamia and forms a monophyletic clade with Ceratozamia and Stangeria. While Stangeria joined the Neotropical cycads Ceratozamia, Zamia and Microcyas, Bowenia grouped with the Southern Hemisphere cycads Encephalartos, Lepidozamia and Macrozamia. All Cycas species formed a distinct clade separated from the other genera. Dioon, on the other hand, was outlying from the rest of Zamiaceae encompassing two major clades—the Southern Hemisphere cycads and the Neotropical cycads. Analysis of the whole cp genomes in phylogeny also supports that the previously recognized family—Stangeriaceae—which contained Bowenia and Stangeria, is not monophyletic. Thus, the cp genome topology obtained in our study is congruent with other molecular phylogenies recognizing only a two-family classification (Cycadaceae and Zamiaceae) within extant Cycadales.

Cinnamomum aromaticum has long been recognized and cultivated in tropical and subtropical Asia for their aromatic bark to produce cinnamon. We reported for the first time the complete plastid genome of C. aromaticum and reconstructed its phylogenetic position. The complete plastid genome is 152,754 bp in length with a quadripartite organization: a large single copy (LSC) region of 93,706 bp and a small single copy (SSC) region of 18,916 bp. Each of the two inverted repeat regions (IRa and IRb) is 20,066 bp. We recovered 128 functional genes, including 84 protein-coding genes, 36 tRNA genes and 8 rRNA genes. The phylogenetic analysis suggested that C. aromaticum and two samples of C. camphora forms a strongly supported clade, which is sister to another cinnamon species of C. verum native to Sri Lanka with strong ultrafast bootstrap support.

The petrophysical and logging response characteristics of asphaltene carbonate reservoirs were examined based on the measurement of porosity and permeability, density, compressional and shear wave slowness, resistivity and Nuclear Magnetic Resonance transverse relaxation time (T2) of cores before and after the bitumen dissolving. The results show that (1) the asphalt can damage the pore structure of the reservoir and cause reduction of effective reservoir space and permeability; (2) with the increase of asphalt content, the compression and shear wave slowness generally decrease while the density and resistivity increase; (3) with the increase of asphalt content, the compressional wave slowness and density change less, while the shear wave slowness and resistivity change larger; and (4) the T2 values of asphalt are generally less than 3 ms, and the higher the maturity of the asphalt, the lower the T2 value. Based on these experiments, a method based on conventional and special logging methods was presented to evaluate asphalt content, effective porosity and water saturation in asphaltene carbonate reservoirs. The method has already been applied to 80 wells in the Longwangmiao Formation of the Anyue gas field in the Sichuan Basin to pick out zones rich in asphalt on the plane, which has effectively guided the selection of well location in the gas reservoir development. Key words: Sichuan Basin, Cambrian Longwangmiao Formation, asphalt, carbonate reservoir, nuclear magnetic resonance logging, petrophysical properties, logging evaluation

Delonix regia, a plant species of the legume family native to Madagascar, has been widely cultivated in the tropical and subtropical regions as an ornamental tree due to its remarkable showy orange-red flowers over summer. Here we report for the first time the complete plastid genome of this species, which has a typical circular structure with a total length of 162,756 bp and contains two inverted repeat regions (IRs, 25,544 bp), a large single copy region (LSC, 92,490 bp), and a small single copy region (SSC, 19,178 bp). The phylogenetic analysis based on the complete plastome sequences of this species and those of the related species from GenBank strongly suggested that D. regia is nested in the subfamily Caesalpinioideae and is sister to a clade consisting of Erythrophlium fordii and the old-sense Mimosoideae.

The dolomite reservoirs of the Lower Cambrian Longwangmiao Fm in the Gaoshiti–Moxi area, Sichuan Basin, are deeply buried (generally 4400–4900 m), with high heterogeneity, making reservoir prediction difficult. In this regard, key seismic exploration technologies were developed through researches. Firstly, through in-depth analysis on the existing geologic, drilling, seismic data and available research findings, basic surface and subsurface structures and geologic conditions within the study area were clarified. Secondly, digital seismic data acquisition technologies with wide azimuth, wide frequency band and minor bins were adopted to ensure even distribution of coverage of target formations through optimization of the 3D seismic geometry. In this way, high-accuracy 3D seismic data can be acquired through shallow, middle and deep formations. Thirdly, well-control seismic data processing technologies were applied to enhance the signal-to-noise ratio (SNR) of seismic data for deep formations. Fourthly, a seismic response model was established specifically for the Longwangmiao Fm reservoir. Quantitative prediction of the reservoir was performed through pre-stack geo-statistics. In this way, plan distribution of reservoir thicknesses was mapped. Fifthly, core tests and logging data analysis were conducted to determine gas-sensitive elastic parameters, which were then used in pre-stack hydrocarbon detection to eliminate the multiple solutions in seismic data interpretation. It is concluded that application of the above-mentioned key technologies effectively promote the discovery of largescale marine carbonate gas reservoirs of the Longwangmiao Fm.

This paper investigates formation tracking control for multi-agent networks with fixed time convergence. The control task is that the follower agents are required to form a prescribed formation within a fixed time and the geometric center of the formation moves in sync with the leader. First, an error system is designed by using the information of adjacent agents and a new control protocol is designed based on the error system and terminal sliding mode control (TSMC). Then, via employing the Lyapunov stability theorem and the fixed time stability theorem, the control task is proved to be possible within a fixed time and the convergence time can be calculated by parameters. Finally, numerical results illustrate the feasibility of the proposed control protocol.

Zenia insignis Chun is a rare and threatened species of the monotypic genus Zenia Chun in the subfamily Dialioideae of Leguminosae. The complete plastid genome of Zenia insignis was sequenced for the first time which also represents the first complete plastid genome of the subfamily Dialioideae. The total length of this genome is 159,358 bp with a large single copy (LSC) region (88,507 bp), a small single copy (SSC) region (18,689 bp), and two inverted repeat regions (IRs, 26,081 bp). We recovered 128 functional genes, including 83 protein-coding genes, 37 tRNA genes and 8 rRNA genes. Phylogenetic analysis strongly supported a sister relationship between Z. insignis and the clade consisting of Caesalpinioideae and Papilionoideae.

Bauhinia × blakeana Dunn, or the Hong Kong Orchid Tree, is a popular ornamental plant in the tropical and subtropical regions. In this study, we report and characterise the complete plastid genome of B. × blakeana in an effort to provide genomic resources for genetic utilization. The complete plastome is 156,100 bp in length and contains the typical quadripartite structure, including two inverted repeat (IR) regions of 25,847 bp, a large single-copy (LSC) region of 86,484 bp and a small single-copy (SSC) region of 17,922 bp. 126 genes are annotated, including 81 protein-coding genes, 37 transfer RNA genes, and eight ribosomal RNA genes. The phylogenetic analysis based on the plastomes from B. × blakeana and 11 previously reported species of Cercidoideae suggested a sister-relationship between B. × blakeana and B. acuminata L. with strong bootstrap support.

This paper reports about a novel three-dimensional chaotic system with three nonlinearities. The system has one stable equilibrium, two stable equilibria and one saddle node, two saddle foci and one saddle node for different parameters. One salient feature of this novel system is its multiple attractors caused by different initial values. With the change of parameters, the system experiences mono-stability, bi-stability, mono-periodicity, bi-periodicity, one strange attractor, and two coexisting strange attractors. The complex dynamic behaviors of the system are revealed by analyzing the corresponding equilibria and using the numerical simulation method. In addition, an electronic circuit is given for implementing the chaotic attractors of the system. Using the new chaotic system, an S-Box is developed for cryptographic operations. Moreover, we test the performance of this produced S-Box and compare it to the existing S-Box studies.