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The unmanned aerial vehicle(UAV) used in agricultural fields usually has a load, which affects stability of flight trajectory. This problem is a great technical challenge and critical issue which has fascinated many researchers in this area. This research paper presents a flight dynamics model for agricultural UAV under load condition. The robust T-S fuzzy control method is applied in the attitude angle control part, and the traditional PID controller is used in the position loop control part. Results of simulation depict that the flight trajectory of agricultural UAV can reach certain stability when the load is relatively small.

Background: Lung adenocarcinoma (LUAD) is a fatal disease with metabolic abnormalities. The dysregulation of S100 calcium‐binding protein A2 (S100A2), a member of the S100 protein family, is connected to the development of various cancers. The impact of S100A2 on the LUAD occurrence and metastasis, however, has not yet been reported. The functional mechanism of S100A2 on LUAD cell metastasis was examined in this article. Methods: The expression of TFAP2A and S100A2 in LUAD tissues and cells was analyzed by bioinformatics and qRT‐PCR, respectively. The enrichment pathway analysis was performed on S100A2. Bioinformatics analysis determined the binding relationship between TFAP2A and S100A2, and their interaction was validated through dual‐luciferase and chromatin immunoprecipitation experiments. Cell viability was determined using cell counting kit‐8 (CCK‐8). A transwell assay was performed to analyze the invasion and migration of cells. Immunofluorescence was conducted to obtain vimentin and E‐cadherin expression, and a western blot was used to detect the expression of MMP‐2, MMP‐9, GLS, and GLUD1. The kits measured the NADPH/NADP ratio, glutathione (GSH)/glutathione disulfide (GSSG) levels, and the contents of glutamine, α‐KG, and glutamate. Results: S100A2 was upregulated in LUAD tissues and cells, and S100A2 mediated glutamine metabolism to induce LUAD metastasis. Additionally, the transcriptional regulator TFAP2A was discovered upstream of S100A2, and TFAP2A expression was upregulated in LUAD, which indicated that TFAP2A promoted the S100A2 expression. The rescue experiment found that upregulation of S100A2 could reverse the inhibitory effects of silencing TFAP2A on glutamine metabolism and cell metastasis. Conclusion: In conclusion, by regulating glutamine metabolism, the TFAP2A/S100A2 axis facilitated LUAD metastasis. This suggested that targeting S100A2 could be beneficial for LUAD treatment. [ABSTRACT FROM AUTHOR]

Blind search for available parking space is accountable for most traffic congestion, accident, and pollution in cities, which severely impact people's life. Parking management based on an online smart parking system is practical to alleviate parking problems in which parking allocation is the core. However, existing researches are weak at satisfying allocation effect and speed simultaneously when solving large-scale dynamic parking allocation problem. To address this problem, we firstly construct an online “Collection-Allocation-Response” smart parking system (CARSP) to offer parking services to users and rent parking spaces from owners so as to obtain revenue for system managers. We then propose a novel Doubly Periodic Rolling Horizon allocation approach (DPRH) that circularly conduct allocation within a short period and reallocation within a long period. We formulate a narrow allocation model (without reallocation) and broad allocation model (with reallocation), both of which are binary integer programming models with the objective of maximizing system integrated benefit. We design seven performance metrics to evaluate the overall allocation effect and speed of CARSP based on DPRH. According to the three-day district-level instance in Beijing, CARSP based on DPRH performs excellently in balancing allocation effect and speed. This study is meaningful for constructing and optimizing an online smart parking system., Author(s): Shangbin Ning [1,2]; Zhenyu Han [1]; Yang Yang [3,4]; Zhenzhou Yuan (corresponding author) [1,2]; Xianyu Wu [1,2] 1. Introduction With the swift development in urbanization and the great growth [...]

Due to the complexity of real optical flow capture, the existing research still has not performed real optical flow capture of infrared (IR) images with the production of an optical flow based on IR images, which makes the research and application of deep learning-based optical flow computation limited to the field of RGB images only. Therefore, in this paper, we propose a method to produce an optical flow dataset of IR images. We utilize the RGB-IR cross-modal image transformation network to rationally transform existing RGB image optical flow datasets. The RGB-IR cross-modal image transformation is based on the improved Pix2Pix implementation, and in the experiments, the network is validated and evaluated using the RGB-IR aligned bimodal dataset M3FD. Then, RGB-IR cross-modal transformation is performed on the existing RGB optical flow dataset KITTI, and the optical flow computation network is trained using the IR images generated by the transformation. Finally, the computational results of the optical flow computation network before and after training are analyzed based on the RGB-IR aligned bimodal data. [ABSTRACT FROM AUTHOR]

In this paper, a self-adaptive, two-stage fuzzy controller is established to realize the real-time online optimization of traffic signal timing plan, which takes multimodels of transportation as the research object to analyze the reliability of the control system at the isolated urban intersection. In this system, the first stage calculates traffic urgency degree for all red phases and selects the red phase with maximum traffic urgency degree as the next green phase. The second stage determines whether to extend or terminate the current signal phase. Aiming at the problems of the parameters of membership functions empirical settings and insufficient response to the real-time fluctuation in traffic flow, the controller introduces an improved hybrid genetic algorithm to solve it and enable the controller to self-learn. Finally, a microsimulation platform is constructed based on the VISSIM and Python language to evaluate the efficiency and reliability of the controller under complex actual traffic conditions. Results showed that the average delay time per vehicle is reduced by 14.59%, while the average number of stops per vehicle is reduced by 0.71% compared with the traditional control method. Results indicate that the traffic signal timing plan generated by the controller can efficiently improve the intersection traffic capacity and has good efficiency and reliability under the condition of medium saturation and unsteady flow., Author(s): Mingzhi Wang [1]; Xianyu Wu (corresponding author) [2]; He Tian [1]; Jie Lin [2]; Meimei He [2]; Liuqing Ding [2] 1. Introduction At present, with the development of shared [...]

Advanced deep learning-based Single Image Super-Resolution (SISR) techniques are designed to restore high-frequency image details and enhance imaging resolution through the use of rapid and lightweight network architectures. Existing SISR methodologies face the challenge of striking a balance between performance and computational costs, which hinders the practical application of SISR methods. In response to this challenge, the present study introduces a lightweight network known as the Spatial and Channel Aggregation Network (SCAN), designed to excel in image super-resolution (SR) tasks. SCAN is the first SISR method to employ large-kernel convolutions combined with feature reduction operations. This design enables the network to focus more on challenging intermediate-level information extraction, leading to improved performance and efficiency of the network. Additionally, an innovative 9 × 9 large kernel convolution was introduced to further expand the receptive field. The proposed SCAN method outperforms state-of-the-art lightweight SISR methods on benchmark datasets with a 0.13 dB improvement in peak signal-to-noise ratio (PSNR) and a 0.0013 increase in structural similarity (SSIM). Moreover, on remote sensing datasets, SCAN achieves a 0.4 dB improvement in PSNR and a 0.0033 increase in SSIM. [ABSTRACT FROM AUTHOR]

Risley-prism-based image sensors can expand the imaging field of view through beam control. The larger the top angle of the prism, the higher the magnification of the field of view, but at the same time, it aggravates the problem of imaging aberrations, which also puts higher requirements on the aberration correction method for the Risley-prism-based image sensor. To improve the speed, accuracy, and stability of the aberration correction process, an automatic calibration method for the Risley-prism-based image sensor is proposed based on a two-axis turntable. The image datasets of the calibration plate with different prism rotation angles and object distances are acquired using a two-axis turntable. Then, the images of the calibration plate are pre-processed using the bicubic interpolation algorithm. The calibration parameters are finally calculated, and parameter optimization is performed. The experimental results verify the feasibility of this automated calibration method. The reprojection error of the calibration is within 0.26 pixels when the distance of the imaging sensor is 3.6 m from the object, and the fine aberration correction results are observed. [ABSTRACT FROM AUTHOR]

Deep-learning-based polarization 3D imaging techniques, which train networks in a data-driven manner, are capable of estimating a target's surface normal distribution under passive lighting conditions. However, existing methods have limitations in restoring target texture details and accurately estimating surface normals. Information loss can occur in the fine-textured areas of the target during the reconstruction process, which can result in inaccurate normal estimation and reduce the overall reconstruction accuracy. The proposed method enables extraction of more comprehensive information, mitigates the loss of texture information during object reconstruction, enhances the accuracy of surface normal estimation, and facilitates more comprehensive and precise reconstruction of objects. The proposed networks optimize the polarization representation input by utilizing the Stokes-vector-based parameter, in addition to separated specular and diffuse reflection components. This approach reduces the impact of background noise, extracts more relevant polarization features of the target, and provides more accurate cues for restoration of surface normals. Experiments are performed using both the DeepSfP dataset and newly collected data. The results show that the proposed model can provide more accurate surface normal estimates. Compared to the UNet architecture-based method, the mean angular error is reduced by 19%, calculation time is reduced by 62%, and the model size is reduced by 11%. [ABSTRACT FROM AUTHOR]

As a efficient and simple design, expander cycle is widely applied in LRE engineering, but it is seldomly used on scramjet research. In order to establish a complete mathematical model for expander cycle scramjet, a control-oriented model for expander cycle scramjet is proposed in this paper. This model consists of four major parts: combustor, cooling channel, turbo pump and nozzle and gives the result of pressure, temperature, mach number and velocity distribution of combustor and cooling channel and is capable of simulate both pure supersonic combustion mode and supersonic shock wave mode of the combustor. Each part is given by specific mathematical description, which contains the calculation of airflow, combustion, heat transfer and thermal cracking of kerosene. By putting all these parts together, a complete model is formed. This model is proposed to calculate the performance and condition of the engine precisely, comprehensively, swiftly and can be directly used in further study.

In the process of unmanned aerial vehicle (UAV) visual-navigation-algorithm design and accuracy verification, the question of how to develop a high-precision and high-reliability semi-physical simulation platform has become a significant engineering problem. In this study, a new UAV semi-physical-simulation-platform architecture is proposed, which includes a six-degree-of-freedom mechanical structure, a real-time control system and real-time animation-simulation software. The mechanical structure can realistically simulate the flight attitude of a UAV in a three-dimensional space of 4 × 2 × 1.4 m. Based on the designed mechanical structure and its dynamics, the control system and the UAV real-time flight-animation simulation were designed. Compared with the conventional simulation system, this system enables real-time flight-attitude simulation in a real physical environment and simultaneous flight-attitude simulation in virtual-animation space. The test results show that the repeated positioning accuracy of the three-axis rotary table reaches 0.006°, the repeated positioning accuracy of the three-axis translation table reaches 0.033 mm, and the dynamic-positioning accuracy reaches 0.04° and 0.4 mm, which meets the simulation requirements of high-precision visual UAV navigation. [ABSTRACT FROM AUTHOR]

We applied a polarization filter array and high-speed camera to the imaging of biological tissues during large, dynamic deformations at 7000 frames per second. The results are compared to previous measurements of similar specimens using a rotating polarizer imaging system. The polarization filter eliminates motion blur and temporal bias from the reconstructed collagen fiber alignment angle and retardation images. The polarization imaging configuration dose pose additional challenges due to the need for calibration of the polarization filter array for a given sample in the same lighting conditions as during the measurement. [ABSTRACT FROM AUTHOR]

Conventional multispectral imaging systems based on bandpass filters struggle to record multispectral videos with high spatial resolutions because of their limited light efficiencies. This paper proposes a multi-aperture multispectral imaging system based on notch filters that overcomes this limitation by allowing light from most of the spectrum to pass through. Based on this imaging principle, a prototype multi-aperture multispectral imaging system comprising notch filters was built and demonstrated. Further, a dictionary learning- and total variation-based spectral super-resolution algorithm was developed to reconstruct spectral images. The simulation results obtained using public multispectral datasets showed that, compared to the dictionary learning-based spectral super-resolution algorithm, the proposed algorithm reconstructed the spectral information with a higher accuracy and removed noise, and the verification experiments confirmed the performance efficiency of the prototype system. The experimental results showed that the proposed imaging system can capture images with high spatial and spectral resolutions under low illumination conditions. The proposed algorithm improved the spectral resolution of the acquired data from 9 to 31 bands, and the average peak signal-to-noise ratio remained above 43 dB, which is 13 dB higher than those of the state-of-the-art coded aperture snapshot spectral imaging methods. Simultaneously, the frame rate of the imaging system was up to 5000 frames/s under natural daylight. [ABSTRACT FROM AUTHOR]

How to sustainably conduct intersection operations is a key issue of the current research. For an actuated control intersection, queued vehicles, control parameters, and phase schemes all affect the operation effect. This paper discusses queued vehicles at actuated intersections and their influence on signal timing. First, this paper establishes an improved traffic wave model and proposes a vehicle queuing model on this basis. Second, by analyzing the queuing and dispersion process of queued vehicles, a minimal green time calculation model is proposed. Then, this paper establishes a maximal green time calculation model aiming at minimizing average vehicle delay and maximizing traffic capacity under different phase schemes, and considers the influence of queued vehicles. Lastly, the models are verified separately; results show that the average error of the minimal green time model was 4.18%, and the average optimization rate of the maximal green time model was 9.27%. It is proved that the models achieved great accuracy and optimization effects, which could potentially improve intersection sustainability. [ABSTRACT FROM AUTHOR]

To compensate for the inability of inexpensive uncooled infrared (IR) sensors to perform high-speed thermography detection with low noise and high sensitivity in the field of non-destructive testing (NDT), a post-processing method for uncooled IR sensors based on compressive sensing is proposed in this paper to perform super-resolution NDT thermography. Super-resolution IR phase images can be generated by first using a sparse representation of the low-resolution (LR) IR images and a sparse dictionary generated from randomly sampled high-resolution (HR) raw training image patches to generate an HR IR image sequence, and, subsequently, implementing IR thermography NDT. To verify the reliability of the proposed method, super-resolution IR images were combined with pulsed phase thermography (PPT) to verify bonded joint structures in carbon fibre-reinforced polymer (CFRP). Compared to other methods, the proposed method reduces the mean square error (MSE) by 11.13% and yields a better visual effect on the PPT phase image reconstructed using three-fold super-resolution. The proposed method not only produces sharp defect edges, but also retains the original texture, which is expected to enable wider application of uncooled IR sensors in NDT applications in the future. [ABSTRACT FROM AUTHOR]

Bandwidth is defined as the maximum amount of green time for a designated movement as it passes through an arterial. In most previous studies, bandwidth has been referred to arterial bandwidth. In practice, a balance between link bandwidth and arterial bandwidth has proven to be important in optimizing coordinated signal timing plans, because not all drivers need to pass through all the intersections on an arterial. This study proposes an algorithm on how to obtain an optimal coordinated signal timing plan with both optimal link bandwidth and optimal arterial bandwidth considering practical vehicles’ speed. The weighted link bandwidth attainability is introduced as an additional measure of effectiveness for assessing the optimization results. The link bandwidth optimization is built based on the improvement of Messer’s algorithm about bandwidth optimization. The arterial bandwidth optimization algorithm takes into consideration the weighted link bandwidth attainability while selecting phase sequences. The proposed algorithm is demonstrated in a case study, and many improvements are archived when a balanced consideration is given to both link bandwidth and arterial bandwidth. Fine-tuning of initial signal timing plan is done using practical travel speed. The evaluation results show a rather significant improvement which is achieved.

Computer-generated hologram (CGH) is a diffractive optical element that has been commonly used as wavefront corrector in the interferometer and can be accurately manufactured to meet the requirements of high-precision detection. But the transmitted wavefront error (TWE) of the CGH substrate and the adjustment errors of cylindrical surface are influence factors of high accuracy measurement. In this paper, we propose the method of calibrating the CGH substrate TWE. After calibrating, the substrate TWE is 0.0052λ (RMS). Meanwhile, we obtain the general expression for the misalignment aberrations by describing the relationship between the wavefront of the measured cylindrical mirror and the corresponding adjustment errors. Then the adjustment errors of the test cylindrical surface can be completely separated by subtracting the fitting function from the measurement on the basis of least-square algorithm. After that, the PV value changes from 3.0565λ to 0.9825λ, and the RMS value changes from 0.5278λ to 0.1273λ, the measurement results have been greatly improved. [ABSTRACT FROM AUTHOR]

Vehicle path recognition is one of the key methods used in urban traffic research, such as traffic flow characteristics analysis. Automatic vehicle identification (AVI) is often used for vehicle path recognition and is suitable for mixed traffic flow with connected automated vehicles (CAVs). However, there still remain issues in overcoming the difficulty of vehicle path identification caused by the discontinuity of AVI data and solving the problem of low precision of AVI application. To model the vehicle path, this paper selects the AVI system of Yicheng Town, Linfen City, Shanxi Province, as a test bed. The travel modes of private cars and taxis are discussed, and the quantified indicators of the model are determined. By combining the analytic hierarchy process (AHP) with the entropy weight method (EWM) to get the weights of the indicators, the path recognition model under incomplete AVI data is proposed. Finally, based on the path recognition model proposed in this paper, case studies are carried out for the private car and taxi path recognition, respectively. The validity of the path identification through practical studies and the effect of the number of missing nodes of AVI equipment on the accuracy of the model are discussed. The results show that the recognition of the travel path using the proposed model is consistent with the actual travel path. The accuracy of the proposed model is more than 60% when the number of missing nodes is less than 7 in total 31 nodes. Considering the decision models for private cars and taxis, respectively, the proposed model provides a method for vehicle path recognition based on incomplete AVI data. [ABSTRACT FROM AUTHOR]

The diversity of endophytic bacteria in the progeny is related to the parental lines. In this study, the traditional separation method was used to study the dominant endophytic bacteria of the shared paternal line and its pollen, different maternal lines and their F1 progeny. And the results showed that the dominant endophytic bacteria in maize seeds and the pollen were Bacillus and Pantoea. The Bacillus diversity of the progeny JMC121 and JN728 were the same as both the paternal line and the maternal line, including Bacillus subtilis, Bacillus velezensis, Bacillus mojavensis, and Bacillus licheniformis. The Bacillus subtilis and Bacillus velezensis in JN828 were the same as both the paternal line and the maternal line, while Bacillus licheniformis was only the same as the paternal line. Through the RAPD molecular typing, there was the same strain of Bacillus mojavensis existed in the paternal line J2416, the pollen and the progeny JN728; this meant that the paternal line passed its dominant endophytic bacteria to the progeny through pollen in vertical transmission. This study showed that the dominant endophytic bacteria in maize seeds and the pollen were Bacillus, and the diversity of F1 progeny was related to both the paternal line and the maternal line. [ABSTRACT FROM AUTHOR]

The integration of automation and information technology in in-situ leached uranium mine was studied, and the solutions were put forward: perfecting the original automation system, perfecting the detection system, and designing a dual control method for material level and pressure during resin reverse transportation to improve transportation efficiency. In the designed information system, the data information was analyzed to find multi-source heterogeneity, and the problem of multi-source heterogeneous data fusion was solved by studying data preprocessing, data storage and management, data analysis and mining. C/S and B/S mode were combined to realize information sharing and interaction. Three levels classification, comprehensive protection, depth defense security protection system was builded. Based on the characteristics of information resource hierarchy, an information platform integrating site layer, control layer, management layer and information decision-making layer was designed. Through the integration design of automation and information technology, data sharing and business collaboration were realized, and the efficiency and quality of decision-making and management were improved. [ABSTRACT FROM AUTHOR]

Daqu provides enzymes and precursors for liquor fermentation, and is the core of liquor fermentation. In this study, 11 Bacillus strains were isolated from sesame-flavored liquor Daqu, which can not only produce protease and amylase, but also have antagonistic effects on common pathogens Escherichia coli and Staphylococcus aureus. According to the gyrA gene phylogeny analysis, these 11 Bacillus strains belong to three species, B1, Y14, Y15, and YPDW9 belong to Bacillus mojavensis, W7, W13, YPDW6, and YPDW12 belong to Bacillus subtilis, and W14, Y5, and YPDW1 belong to Bacillus velezensis. According to the results of random amplified polymorphic DNA (RAPD) typing, there are three strains in Bacillus mojavensis, among which Y14 and Y15 are the same ones. All four Bacillus subtilis strains and three Bacillus velezensis strains are different. The specific primers were used to randomly amplify the biological control genes expressing lipopeptide antibiotics (bioA, bmyB, ituC, fenD, srfAA, srfAB, yngG,and yndJ), and the results showed that antagonistic genes other than fenD gene were amplified in four Bacillus mojavensis strains; Bacillus subtilis amplification was significantly different, but srfAA, bmyB and yndJ genes were all present; All genes were amplified in Bacillus velezensis except YPDW1 without ituC. This research provides new ideas for strengthening Daqu and lays a foundation for improving the quality of liquor. [ABSTRACT FROM AUTHOR]

Nowadays, parking spaces are scarce resources in urban cities. Travelers often spend too much time looking for available parking spaces, which increases travel time of travelers and results in additional traffic congestion. With the innovation and application of intelligent parking technology, parking spaces can be booked in the system in advance through mobile phone, which will greatly reduce the time for drivers to cruise and search for parking spaces. Targeted at the serious waste of parking resources, traffic congestion caused by too intensive parking demand in time and space, a parking allocation model considering the ability of dynamic and static traffic conversion is established with the goal of minimizing the total travel time of the travelers. Based on the dynamic traffic distribution model, considering the constraints of capacity of the road link, parking lot entrance and the number of the parking spaces in parking lot, the dynamic and static traffic is combined by considering the parking lot connection section as a conversion link to be added into the traffic network. And the solution method based on particle swarm optimization is proposed. Experimental results on a case (Beijing Chaoyang Joy City and surrounding parking lots) show that our parking allocation model works satisfactorily by effectively reducing the travel time of travelers and increase customer arrivals in shopping centers. From the point of view of traffic managers, the model can make the parking occupancy of all parking lots more balanced, which indicates that the model can help to better coordinate the available parking resources. In summary, the model proposed in this paper can not only divert the flow beyond the capacity of the road facilities at the connection of the parking lot, but also balance the utilization rate of the surrounding parking resources and reduce the dynamic traffic pressure, it is a proper way to develop the sustainable transportation. [ABSTRACT FROM AUTHOR]

The use of kerosene-based regenerative cooling for scramjet has been found widespread attention due to its inherent nature of high energy utilization efficiency and good thermal protection performance. In order to provide a reference for the later design and experiments, three-dimensional turbulence simulations and sensitivity analysis were performed to determine the effects of three operating mode parameters, heat flux, mass flow rate, and outlet pressure, on the regenerative cooling characteristics of kerosene scramjets. A single rectangular-shaped channel for regenerative cooling was assumed. The RNG k-ε turbulence model and kerosene cracking mechanism with single-step global reaction were applied for the supercritical-pressure heat transfer of kerosene flows in the channel. Conclusions can be drawn that as the kerosene temperature rises along the channel, the decrease of fluid density and viscosity contributes to increasing the fluid velocity and heat transfer. When the kerosene temperature is close to the pseudocritical temperature, the pyrolysis reaction results into the rapid increase of fluid velocity. However, the heat transfer deterioration occurs as the specific heat and thermal conductivity experience their turning points. The higher heat flux leads to lower heat transfer coefficient, and the latter stops rising when the wall temperature reaches the pseudocritical temperature. The same rising trend of the heat transfer coefficient is observed under different outlet pressures, but the heat transfer deterioration occurs earlier at smaller outlet pressure for the reason that the corresponding pseudocritical temperature decreases. The heat transfer coefficient increases significantly along with the rise of the mass flow rate, which is mainly attributable to the increase of Reynolds number. Quantitative results indicate that as the main influence factors, the heat flux and mass flow rate are respectively negatively and positively relative to the intensification of heat transfer, but outlet pressure always has little effects on cooling performance. [ABSTRACT FROM AUTHOR]

In order to accurately divide the traffic control subarea and improve the regional coordination control effect, this paper studies the key technologies of traffic control subarea division from the influence of the discrete characteristics of the fleet on the coordinated control. Correlation analysis method and regression analysis method are used to construct the correlation model of adjacent intersections. The principle and process of transportation subarea division are designed by using analytic hierarchy process, and a new traffic subarea division model is proposed. Taking Gulou Street in Miyun District of Beijing as an example, combined with the green wave coordination optimization method, the new model was applied and simulated in SimTraffic. The simulation results show that the average delay of the intersection is reduced by 21.4%, the total number of stops is reduced by 9.62%, and the travel time is shortened by 8.75%. The new intersection degree model and the coordinated control scheme obtained by the traffic subarea division model make the highest traffic efficiency. That is, to verify the scientific research method of this paper, the research results are reliable and the practical application value is high. [ABSTRACT FROM AUTHOR]

Maize is a crop grown worldwide. Bacillus ciccensis 5L6T was isolated from maize (Zea mays L., Jingke968) seeds and was a new species of Bacillus with potential anti-fungal activity. The complete genome of 5L6T was sequenced and assembled with a length of 5,207,802 bp and a GC content of 37.42%. The proteins responsible for anti-fungal activity and the potential beneficial interaction with maize of 5L6Twere annotated and reported here. The complete genome sequence of the new species B. ciccensis 5L6T will promote its biological application. [ABSTRACT FROM AUTHOR]