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To demonstrate the feasibility and improve the implementation of laser weeding, a static movable lift-adjustable closed fiber laser weeding device and system have been developed, followed by experiments and performance evaluations. Physical experiments were conducted on the energy required for laser cutting of weed stems, targeting four common larger weeds (Chenopodium album, Amaranthus spinosus, Setaria viridis, and Eleusine indica) in farmland and orchards. At the same irradiation distances, the energy required to cut the same type of large weed generally increases with increasing distances and stem diameters but decreases with increasing irradiation time. The variance of stems' power density after irradiation was larger and the values were more dispersed for Chenopodium album and Setaria viridis weeds, and the values were relatively scattered, while the power density values of Amaranthus spinosus and Eleusine indica weeds were more concentrated. When the irradiation time was 10 s, the 3.892 W/mm2 laser was sufficient to eliminate weeds and plants with the irradiation distances of 2 m. The 2.47 W/mm2 laser was more effective, as it killed weeds within a distance of 1 m in less than 1 s. This work demonstrates the feasibility of the laser weeding device and system that can completely cut off the stems of large weeds, and this technology has the potential to promote sustainable agriculture. [ABSTRACT FROM AUTHOR]

The most important part of fruit cultivation is transplanting, which can be completed efficiently by an automatic transplanter. In this study, an automatic solanum lycopersicum transplanter was developed. It is primarily composed of the following devices: a seedling tray fixator, a mechanical transplanting arm, double horizontal driving modules, double vertical driving cylinders, a seedling separation device, double-crank five-bar planting devices, a power distribution system, and a PLC control system. An experimental test on an automatic transplanter was carried out on dry land. The experimental results showed that when the planting frequency was 80 plants/(min·row), the transplanting success rate was 93.89%, the missed planting rate was 1.58%, the replanting rate was 0.65%, the lodging rate was 1.94%, and the exposed seedling rate was 1.94%. Each device of the automatic transplanter was coordinated to complete the transplanting process. The automatic transplanter met the operation requirements, and it not only transplanted in dry land but also provided a theoretical basis for fruit cultivation in solar greenhouses in the future. [ABSTRACT FROM AUTHOR]

Accurate positioning at the inter-row canopy can provide data support for precision variable-rate spraying. Therefore, there is an urgent need to design a reliable positioning method for the inter-row canopy of closed orchards (planted forests). In the study, the Extended Kalman Filter (EKF) fusion positioning method (method C) was first constructed by calibrating the IMU and encoder with errors. Meanwhile, 3D Light Detection and Ranging (LiDAR) observations were introduced to be fused into Method C. An EKF fusion positioning method (method D) based on 3D LiDAR corrected detection was designed. The method starts or closes method C by the presence or absence of the canopy. The vertically installed 3D LiDAR detected the canopy body center, providing the vehicle with inter-row vertical distance and heading. They were obtained through the distance between the center of the body and fixed row spacing. This can provide an accurate initial position for method C and correct the positioning trajectory. Finally, the positioning and canopy length measurement experiments were designed using a GPS positioning system. The results show that the method proposed in this study can significantly improve the accuracy of length measurement and positioning at the inter-row canopy, which does not significantly change with the distance traveled. In the orchard experiment, the average positioning deviations of the lateral and vertical distances at the inter-row canopy are 0.1 m and 0.2 m, respectively, with an average heading deviation of 6.75°, and the average relative error of canopy length measurement was 4.35%. The method can provide a simple and reliable inter-row positioning method for current remote-controlled and manned agricultural machinery when working in standardized 3D crops. This can modify the above-mentioned machinery to improve its automation level. [ABSTRACT FROM AUTHOR]

The purpose of constructing onboard observation mission queues is to improve the execution efficiency of onboard tasks and reduce energy consumption, representing a significant challenge in achieving efficient global military reconnaissance and target tracking. Existing research often focuses on the aspect of task scheduling, aiming at optimizing the efficiency of single-task execution, while neglecting the complex dependencies that might exist between multiple tasks and payloads. Moreover, traditional task scheduling schemes are no longer suitable for large-scale tasks. To effectively reduce the number of tasks within the network, we introduce a network aggregation graph model based on multiple satellites and tasks, and propose a task aggregation priority dynamic calculation algorithm based on graph computations. Subsequently, we present a dynamic merging-based method for multi-satellite, multi-task aggregation, a novel approach for constructing onboard mission queues that can dynamically optimize the task queue according to real-time task demands and resource status. Simulation experiments demonstrate that, compared to baseline algorithms, our proposed task aggregation method significantly reduces the task size by approximately 25% and effectively increases the utilization rate of onboard resources. [ABSTRACT FROM AUTHOR]

A novel indoor positioning method for a pigsty based on ultra-wideband (UWB) technology is proposed via reasonably arranging the base stations and positioning tags, which can provide strong support for the accurate positioning of specific pig pens in the pig house. The distribution of Dilution of Precision (DOP) values is analyzed in different deployment schemes which include the amount, the height, the deployment shape, and the distance of the base stations through positioning simulation. Moreover, the positioning effect of dynamic following positioning, the root-mean-square error (RMSE), and the variance of static positioning are measured. It is noteworthy that the Kalman filtering algorithm is adopted to smooth the dynamic following positioning experimental data for reducing the positioning error. The simulated results show that the DOP values decrease with the increase in height and distance, and these results and laws are consistent with the experimental results. However, the DOP values are best reached when the height is from 1.75 m to 2.75 m, and the distance is over 3.00 m. Furthermore, the DOP values of quadrilateral deployment are smaller than the ones of triangular deployment. In addition, the variance of static positioning and dynamic following positioning is decreased by utilizing the Kalman filtering algorithm. Therefore, the excellent positioning system and its solutions in a pigsty can be provided by our proposed indoor positioning method. [ABSTRACT FROM AUTHOR]

Socially regulated learning (SoRL) is an important way to maintain the sustainable development of collaborative learning (CL). Usually, learners can achieve sustainable and high-quality SoRL with the intervention of teachers. To improve the appropriateness of the intervention, teachers need to clarify the profiles of SoRL to which learners belong, as well as the influence of collaborative learning motivation (CLM) and the relevant background variables. This study used three non-duplicate samples to provide evidence for the psychometric properties of the SoRL and CLM scales through item analysis, exploratory factor analysis (sample 1, n = 531), and confirmatory factor analysis (sample 2, n = 1278). The profiles of SoRL among university students were determined through latent profile analysis (sample 3, n = 909). This study identified three profiles of regulation (strong SoRL, progressive SoRL, and weak SoRL). The analysis of multivariate variance and multiple logistic regression methods further explored the differences in the dimensions of SoRL structures across different profiles and the extent to which CLM and background variables predicted profiles. The results showed that collaborative motivation (CM) and learning motivation (LM) were the predictors of learners' transformation from a low regulation level to a medium regulation level. CM, LM, altruistic motivation, and major background were the predictors of learners' transition from the medium regulation level to the high regulation level. Accordingly, teachers can provide learners with an appropriate external intervention to promote the improvement of SoRL. This study contributes to improving learners' SoRL levels and promoting the sustainable development of education. In the future, the changing characteristics of learners' SoRL profiles over time will be explored, and the application of learning process data will be strengthened. [ABSTRACT FROM AUTHOR]

Cross-lingual text summarization is a highly desired service for overseas report editing tasks and is formulated in a distributed application to facilitate the cooperation of editors. The multilanguage pre-trained language model (MPLM) can generate high-quality cross-lingual text summaries with simple fine-tuning. However, the MPLM does not adapt to complex variations, like the word order and tense in different languages. When the model performs on these languages with separate syntactic structures and vocabulary morphologies, it will lead to the low-level quality of the cross-lingual summary. The matter worsens when the cross-lingual summarization datasets are low-resource. We use a knowledge distillation framework for the cross-lingual summarization task to address the above issues. By learning the monolingual teacher model, the cross-lingual student model can effectively capture the differences between languages. Since the teacher and student models generate summaries in two languages, their representations lie on different vector spaces. In order to construct representation relationships across languages, we further propose a similarity metric, which is based on bidirectional semantic alignment, to map different language representations to the same space. In order to improve the quality of cross-lingual summaries further, we use contrastive learning to make the student model focus on the differentials among languages. Contrastive learning can enhance the ability of the similarity metric for bidirectional semantic alignment. Our experiments show that our approach is competitive in low-resource scenarios on cross-language summarization datasets in pairs of distant languages. [ABSTRACT FROM AUTHOR]

Extensive research has been conducted on the effects of pollen activation temperature, cultivation temperature, and ambient temperature on germination rates and fruit sets. Yet, the influence of the temperature (pre-germination temperature) at which the pollen suspension is prepared within the storage container (tank) remains unexplored. In this study, we initially established the optimal time for pollen activation. Subsequently, pollen suspensions at varying temperatures were prepared, and their germination rates were analyzed using microscopy. Pollen suspensions of different temperatures were then sprayed onto Fojianxi pear flowers, and parameters such as flower fruit set rate, inflorescence fruit set rate, fruit longitudinal dimension, fruit transverse dimension, and fruit shape index were evaluated. The findings revealed that the optimal pollen activation duration was 6 h. A pollen suspension temperature of 30 °C resulted in the highest germination rate (72.06 ± 6.87%). However, a suspension temperature of 25 °C achieved the highest flower fruit set rate (57.29 ± 5.58%) and inflorescence fruit set rate (87.50 ± 4.84%). The fruit longitudinal dimension (68.12 ± 3.94 mm), transverse dimension (73.77 ± 4.04 mm), and fruit shape index (108.42 ± 6.02%) were most favorable at a suspension temperature of 15 °C. Our study concludes that the pollen in lower pollen suspension temperatures (15~25 °C) has higher germination energy and have higher stigmatic capacity. Thus, we advocate for a pollen suspension temperature range of 15~25 °C when employing liquid spray pollination techniques with Xuehuali (Pyrus bretschneiderilia) pollen. [ABSTRACT FROM AUTHOR]

With the aim of solving the problems of high labor intensity, low operational efficiency, and poor deposition distribution uniformity in the mango canopy associated with traditional plant protection devices, an air-ground co-operation stereoscopic plant protection system consisting of an orchard caterpillar mist sprayer and a six-rotor plant protection UAV was designed to jointly undertake plant protection operations in mango orchards. We tested the spraying performance of the system on mango trees, compared with the single-machine operation, the air–ground co-operation system could significantly increase the droplet coverage on the upperside of mango leaves in each part of the canopy (a 14.7% increase for the mist sprayer and 12.9% for the UAV). This increased the active component deposition distribution uniformity in the mango canopy but could not significantly improve the deposition and coverage of droplets on the underside of leaves compared with the mist sprayer and plant protection UAV. Due to the characteristics of the mango canopy such as large leaf length and thickness and complex leaf inclination distribution, this led to poor deposition distribution uniformity of the two spray units, and the overall CV was over 150%. The pesticide active ingredients were almost uniformly distributed in the vertical direction when the application ratios (ground implements/plant protection drones) were 8/2 and 7/3, offering a promising protocol for reduced pesticide application in mango orchards. This study presents promising data that support the innovative integration of drones into crop protection programs for large canopy crops (e.g., mango) and provides guidance for the ACSPPS system in reduction and precision application research. [ABSTRACT FROM AUTHOR]

Male mammals display different paternal responses to pups, either attacking or killing the young offspring, or contrastingly, caring for them. The neural circuit mechanism underlying the between-individual variation in the pup-directed responsiveness of male mammals remains unclear. Monogamous mandarin voles were used to complete the present study. The male individuals were identified as paternal and infanticidal voles, according their behavioral responses to pups. It was found that the serotonin release in the medial preoptic area (MPOA), as well as the serotonergic neuron activity, significantly increased upon licking the pups, but showed no changes after attacking the pups, as revealed by the in vivo fiber photometry of the fluorescence signal from the 5-HT 1.0 sensor and the calcium imaging indicator, respectively. It was verified that the 5-HTergic neural projections to the MPOA originated mainly from the ventral part of the dorsal raphe (vDR). Furthermore, the chemogenetic inhibition of serotonergic projections from the vDR to the MPOA decreased the paternal behaviors and shortened the latency to attack the pups. In contrast, the activation of serotonergic neurons via optogenetics extended the licking duration and inhibited infanticide. Collectively, these results elucidate that the serotonergic projections from the vDR to the MPOA, a previously unrecognized pathway, regulate the paternal responses of virgin male mandarin voles to pups. [ABSTRACT FROM AUTHOR]

Satellite network is considered a prominent architecture for future space-air-ground integrated networks, where the relay satellite network (RSN) plays an essential role in data transmission. However, the relay satellite network faces practical challenges. First, due to the dynamic network topology and limited resources such as storage capacity, antennas, and bandwidth, optimizing data transmission and resource allocation in a resource-constrained stochastic system is challenging. Second, satellites intermittently enter the eclipse zone, which leads to an unstable energy supply. Therefore, optimal energy management is required to balance energy supply and consumption. In this paper, we proposed an online optimal control algorithm, based on Lyapunov stability theory, to optimize data transmission and energy management jointly. Furthermore, the performance of our proposal is analyzed comprehensively, including the reasonable bounds for data and energy and the optimality of our proposed algorithm. Finally, extensive performance evaluation simulations are performed based on real-world satellite parameters. The simulation results indicate that the proposed method can achieve long-term network stability and energy sustainability. Moreover, the proposed algorithm shows an improvement of 9.6% and 20.3% in system utility compared to the non-optimized transmission method and non-optimized energy management algorithm, respectively. [ABSTRACT FROM AUTHOR]

Optical and Synthetic Aperture Radar (SAR) images are highly complementary, and their registrations are a fundamental task for other remote sensing applications. Traditional feature-matching algorithms fail to solve the significant nonlinear radiation difference (NRD) caused by different sensors. To address this problem, a robust registration algorithm with the multi-scale orientated map of phase congruency (MSPCO) is proposed. First, a nonlinear diffusion scale space is established to obtain the scale invariance of feature points. Compared with the linear Gaussian scale space, the nonlinear diffusion scale space can better preserve the edge and texture information. Second, to ensure the quantity and repeatability of features, corner points and edge points are detected on the moment map of phase congruency, respectively, which is the foundation to the next feature matching. Third, the MSPCO descriptor is constructed via the orientation of phase congruency (PCO). PCO is highly robust to NRD, and the different scales of PCOs enhance the robustness of the descriptor. Finally, a feature-matching strategy based on an effective scale ratio is proposed, which reduces the number of comparisons among features and improves computational efficiency. The experimental results show that the proposed method is better than the existing feature-based methods in terms of the number of correct matches and registration accuracy. The registration accuracy is only inferior to that of the most advanced template matching method, and the accuracy difference is within 0.3 pixels, which fully demonstrates the robustness and accuracy of the proposed method in optical and SAR image registration. [ABSTRACT FROM AUTHOR]

Liquid spray pollination (LSP) is widely used in fruit tree pollination. However, the LSP parameters that affect the pollen activity are still unclear. In this study, three LSP parameters that mainly affect the pollen activity were studied: storage time of pollen suspensions, sprayer parameters and unmanned aerial vehicle sprayer (UAVS) downwash airflow. In addition, sprayer parameters include the recirculation device, pump type, spraying pressure, nozzle size and revolutions per minute (rpm) of the rotary atomizer (RA). The results showed that, with the exception of nozzle size and UAVS downwash airflow, the pollen activity was significantly influenced by LSP parameters. The mean pollen activity decreased by 20.20% when the pollen suspension was stored for 30 min compared to 0 min. The activity of pollen in the tank was dramatically reduced using the recirculation device. The mean pollen activity decreases as the pump production maximum pressure increases. The mean pollen activity decreased from 40.7% to 29.02% when the spraying pressure increased from 0.3 MPa to 2.5 MPa. Additionally, the mean pollen activity decreased from 44.25% to 14.14% as the rpm of RA increased from 3000 rpm to 14,000 rpm. Our study demonstrated that pollen activity would be ensured by appropriate LSP parameters. This study provides a reliable theoretical basis for optimizing and advancing pear LSP technology. [ABSTRACT FROM AUTHOR]

Naringin (Nar) is a dihydroflavonoid compound, widely found in citrus fruit and used in Chinese herbal medicine. As a phytochemical, it acts as a dietary supplement that can delay aging and prevent aging-related disease, such as obesity and diabetes. However, its exact mechanism remains unclear. In this study, the high-glucose-induced (HGI) Caenorhabditis elegans model was used to evaluate the anti-aging and anti-obesity effects of Nar. The mean lifespan and fast movement span of HGI worms were extended roughly 24% and 11%, respectively, by Nar treatment. Oil red O staining revealed a significant reduction in fat accumulation and dFP::LGG-labeled worms showed the promotion of autophagy. Additionally, whole transcriptome sequencing and gene set variation analysis suggested that Nar upregulated the lipid biosynthesis and metabolism pathways, as well as the TGF-β, Wnt and longevity signaling pathways. Protein–protein interaction (PPI) network analysis identified hub genes in these pathways for further analysis. Mutant worms and RNA interference were used to study mechanisms; the suppression of hlh-30, lgg-1, unc-51, pha-4, skn-1 and yap-1 disabled the fat-lowering, lifespan-prolonging, and health-promoting properties of Nar. Collectively, our findings indicate that Nar plays an important role in alleviating HGI-aging and anti-obesity effects by reducing fat accumulation and promoting autophagy. [ABSTRACT FROM AUTHOR]

With satellite systems rapidly developing in multiple satellites, multiple tasks, and high-speed response speed requirements, existing computing techniques face the following challenges: insufficient computing power, limited computing resources, and weaker coordination ability. Meanwhile, most methods have more significant response speed and resource utilization limitations. To solve the above problem, we propose a distributed collaborative computing framework with a genetic algorithm-based task scheduling model (DCCF-GA), which can realize the collaborative computing between multiple satellites through genetic algorithm. Specifically, it contains two aspects of work. First, a distributed architecture of satellites is constructed where the main satellite is responsible for distribution and scheduling, and the computing satellite is accountable for completing the task. Then, we presented a genetic algorithm-based task scheduling model that enables multiple satellites to collaborate for completing the tasks. Experiments show that the proposed algorithm has apparent advantages in completion time and outperforms other algorithms in resource efficiency. [ABSTRACT FROM AUTHOR]

The increasing number of satellites for specific space tasks makes it difficult for traditional satellite task planning that relies on ground station planning and on-board execution to fully exploit the overall effectiveness of satellites. Meanwhile, the complex and changeable environment in space also poses challenges to the management of multi-satellite systems (MSS). To address the above issues, this paper formulates a mixed integer optimization problem to solve the autonomous task planning for MSS. First, we constructed a multi-agent-based on-board autonomous management and multi-satellite collaboration architecture. Based on this architecture, we propose a hybrid genetic algorithm with simulated annealing (H-GASA) to solve the multi-satellite cooperative autonomous task planning (MSCATP). With the H-GASA, a heuristic task scheduling scheme was developed to deal with possible task conflicts in MSCATP. Finally, a simulation scenario was established to validate our proposed H-GASA, which exhibits a superior performance in terms of computational power and success rate compared to existing algorithms. [ABSTRACT FROM AUTHOR]

Anti-sorting signal design is an important direction of radio frequency (RF) stealth signal design. The RF stealth signal design is based on the anti-sorting signal design principle, which is essentially the failure principle of the radar signal sorting algorithm. Cluster pre-sorting, the key to radar signal sorting, has the advantages of fast sorting, simultaneous sorting of multiple sources, and greatly reduced computational pressure of the main sorting. However, a unified and widely applicable cluster-sorting failure principle guiding the anti-sorting signal design has not been formally reported in RF stealth anti-sorting signal design. In this paper, the principles of the data field-based K-means clustering algorithm and the fuzzy C-means clustering algorithm are first studied. Aiming at the key step of data similarity measurement in the clustering algorithm, the failure principle of cluster sorting based on pseudo-center wide-agile multi-dimensional compound modulation is proposed. This principle can correctly guide the design of the anti-clustering sorting signal, so it is also called the design principle of the RF stealth anti-sorting signal based on pseudo-center wide-agile multi-dimensional compound modulation. The correctness of the principle is proved by formula derivation, signal simulation, and a sorting experiment. Through a signal comparison simulation with random interference pulse anti-sorting signals, it is strongly proved that the anti-sorting performance of signals designed under the guidance of the anti-clustering signal design principle proposed in this paper is stronger than that of random interference pulse signals. This study provides theoretical support for designing RF stealth anti-sorting signals. Using the signal design principle proposed in this paper, the anti-sorting performance of the RF stealth signal is improved by 10%. The principle of signal design helps to improve design efficiency. [ABSTRACT FROM AUTHOR]

Automatic navigation (AN) is an essential component to ensure the safety of pesticide application in orchards, whereas precision variable-rate spraying (PVS) serves as an indispensable technology for reducing the application of pesticides and protecting the environment. At present, AN and PVS are not closely combined. In this case, a single three-dimension (3D) light detection and ranging (LIDAR) sensor is hereby adopted to sense the information of fruit trees around the robot and determine the region of interest (ROI). Moreover, two-dimensional (2D) processing is conducted over the point clouds within the ROI to obtain the center-of-mass coordinates of fruit trees, and determine the vertical distance of the robot to the center line of the fruit tree row (FTR) based on the FTR on both sides using the Random Sample Consensus (RANSAC) algorithm. Then, the robot is controlled to drive along the center line of the FTR. At the same time, the speed and position of the robot are determined by the encoder and inertial measurement unit (IMU), and the IMU corrects the information collected from the zoned canopy of the fruit trees. The results present a lateral deviation (LD) of less than 22 cm and a course deviation (CD) of less than 4.02° during AN. Compared with the traditional spraying (TS), the PVS applies 32.46%, 44.34% and 58.14% less pesticide application, air drift and ground loss, respectively. With the spraying effect guaranteed, the single 3D LIDAR, the encoder and IMU realize the AN and PVS of the robot, reduce the volume of pesticide application, ground loss and air drift, and effectively control the pollution caused by pesticides to the environment. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) stealth anti-sorting technology is a research hotspot in the radar field. In this study, the signal design principles of anti-cluster and anti-SDIF sorting were investigated for processes of clustering pre-sorting and sequence-difference-histogram main sorting. Then, in accordance with the signal design principle, a 2D interleaving feedback hyperchaotic system based on the cosine-exponential was designed. A method to modulate the pulse repetition interval (PRI) of the signal parameters and carrier frequency with wide intervals through the hyperchaotic system was developed. Finally, we verified the correctness of the signal design principle, the performance of the hyperchaotic system, and the anti-sorting performance of the designed signal using simulations. The results showed that the signal design principle could guide the signal design. The hyperchaotic system outperformed the classical 1D and 2D chaotic systems and the classical 3D Lorenz systems in terms of randomness and complexity. Anti-cluster sorting and anti-SDIF sorting could be realized by anti-sorting signals modulated by a hyperchaotic system, with the anti-SDIF sorting performance being better than that of the PRI random jitter signal. [ABSTRACT FROM AUTHOR]

Clinopodii herba is a folk herbal medicine for treatments of hemorrhagic disorders. However, there is not even a quantitative standard for clinopodii herba deposited in the Chinese Pharmacopoeia. The development of a strategy for rapid and efficient extraction and simultaneous detection of multiple components in clinopodii herba is therefore of great value for its quality evaluation. Here, a variable wavelength strategy was firstly applied to quantity multiple components by segmental monitoring by UHPLC with diode array detector following ultrasound-assisted extraction. The parameters of ultrasound-assisted extraction were optimized using single factor optimization experiments and response surface methodology by a Box–Behnken design combined with overall desirability. Subsequently, a rapid, efficient, and sensitive method was applied for simultaneous determination of eleven compounds, which represented the major and main types of components in clinopodii herba. Moreover, the performance of the validated method was successfully applied for the quality control of various batches of clinopodii herba and provided sufficient supporting data for the optimum harvest time. The Box-Behnken-optimized ultrasound-assisted extraction coupled with variable wavelength detection strategy established in this work not only improves the quality control of clinopodii herba, but also serves as a powerful approach that can be extended to quality evaluation of other traditional Chinese medicines. [ABSTRACT FROM AUTHOR]

As electronic warfare becomes the core of modern warfare, radio frequency (RF) stealth radar is becoming the focus of modern electronic warfare. The anti-sorting strategy of RF stealth radar is a new effective method of the anti-enemy electronic reconnaissance system. Hence, research on the failure mechanism of sorting algorithms has become the cornerstone of anti-sorting technology. In this paper, the mechanism of algorithm failure is studied because the SDIF algorithm is widely used in engineering practice throughout the whole workflow of the sequential difference histogram (SDIF) algorithm, from the estimation of pulse repetition interval (PRI) destroyed by the algorithm and algorithm analysis to the staggered signal. Firstly, the working steps of the SDIF histogram sorting algorithm are considered. Key steps of signal sorting by the algorithm are analyzed, and the failure principle of the sorting algorithm is proposed. It is pointed out that if the PRI signal center value of the two groups of radars is within the tolerance range of the sorting algorithm, when the two signal center values are not of the same order of magnitude, the difference is more than 10 times, and the signal variation is less than 30% of the center value, the sorting error of the algorithm for the radar signal is at least 25%. The sorting algorithm fails to sort signals. At the same time, for the sorting failure of the staggered signal, the sub-PRI design formula of the staggered signal is proposed, and the staggered signal satisfying the design formula can make the sorting algorithm invalid. Finally, the correctness of the SDIF failure principle is further verified by formula derivation, signal design simulation and experiment. The principle of sorting failure provides theoretical support and foundation for the design of anti-sorting RF stealth signal. The principle of sorting failure makes up for the shortcomings of random signal design and improves the design efficiency of RF stealth signal. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) stealth is one of the essential research hotspots in the radar field. The anti-sorting signal is an important direction of the RF stealth signal. Theoretically speaking, the anti-sorting signal design is based on the failure principle of the radar signal sorting algorithm, and the SDIF algorithm is a core sorting algorithm widely used in engineering. Thus, in this paper, the SDIF algorithm is first analyzed in detail. It is pointed out that the threshold function of the SDIF algorithm will fail when the signal pulse repetition interval (PRI) value obeys the interval distribution whose length is 20 times larger than the minimum interval of PRI. Secondly, the correctness of the failure principle of SDIF threshold separation is proved by the formula. Finally, the correctness is further verified by the signal design case. The principle of SDIF sorting threshold failure provides theoretical support for anti-sorting RF stealth signal design. It also complements the shortcoming of the casual design for the anti-sorting signal. Furthermore, the principle of SDIF sorting threshold failure helps improve anti-sorting signal design efficiency. Compared with the Dwell & Switch (D&S) signal and jitter signal, the anti-sorting ability of the signal designed by using the sorting failure principle is notably enhanced through simulation and experimentation. [ABSTRACT FROM AUTHOR]

Fourier ptychographic microscopy (FPM) is a potential imaging technique, which is used to achieve wide field-of-view (FOV), high-resolution and quantitative phase information. The LED array is used to irradiate the samples from different angles to obtain the corresponding low-resolution intensity images. However, the performance of reconstruction still suffers from noise and image data redundancy, which needs to be considered. In this paper, we present a novel Fourier ptychographic microscopy imaging reconstruction method based on a deep multi-feature transfer network, which can achieve good anti-noise performance and realize high-resolution reconstruction with reduced image data. First, in this paper, the image features are deeply extracted through transfer learning ResNet50, Xception and DenseNet121 networks, and utilize the complementarity of deep multiple features and adopt cascaded feature fusion strategy for channel merging to improve the quality of image reconstruction; then the pre-upsampling is used to reconstruct the network to improve the texture details of the high-resolution reconstructed image. We validate the performance of the reported method via both simulation and experiment. The model has good robustness to noise and blurred images. Better reconstruction results are obtained under the conditions of short time and low resolution. We hope that the end-to-end mapping method of neural network can provide a neural-network perspective to solve the FPM reconstruction. [ABSTRACT FROM AUTHOR]

As an essential element, the effect of Phosphorus (P) on plant growth is very significant. In the early growth stage of maize, it has a high sensitivity to the deficiency of phosphorus. The main purpose of this paper is to monitor the maize status under two phosphorus levels in soil by a nondestructive testing method and identify different phosphorus treatments by spectral data. Here, the Analytical Spectral Devices (ASD) spectrometer was used to obtain canopy spectral data of 30 maize inbred lines in two P-level fields, whose reflectance differences were compared and the sensitive bands of P were discovered. Leaf Area Index (LAI) and yield under two P levels were quantitatively analyzed, and the responses of different varieties to P content in soil were observed. In addition, the correlations between 13 vegetation indexes and eight phenotypic parameters were compared under two P levels so as to find out the best vegetation index for maize characteristics estimation. A Back Propagation (BP) neural network was used to evaluate leaf area index and yield, and the corresponding prediction model was established. In order to classify different P levels of soil, the method of support vector machine (SVM) was applied. The results showed that the sensitive bands of P for maize canopy included 763 nm, 815 nm, and 900–1000 nm. P-stress had a significant effect on LAI and yield of most varieties, whose reduction rate reached 41% as a whole. In addition, it was found that the correlations between vegetation indexes and phenotypic parameters were weakened under low-P level. The regression coefficients of 0.75 and 0.5 for the prediction models of LAI and yield were found by combining the spectral data under two P levels. For the P-level identification in soil, the classification accuracy could reach above 86%. These abilities potentially allow for phenotypic parameters prediction of maize plants by spectral data and different phosphorus contents identification with unknown phosphorus fertilizer status. [ABSTRACT FROM AUTHOR]

To overcome the low timeliness of resource scheduling problems in spatial information networks, we propose a method based on a dynamic reconstruction of resource request queues and the autonomous coordinated scheduling of resources. First, we construct a small satellite network and combine the graph maximum flow theory to solve the link resource planning problem during inter-satellite data transmission. In addition, we design a multi-satellite resource scheduling algorithm with minimal time consumption based on graph theory. The algorithm is based on graph theory to reallocate the resource request queue to satellites with idle processing resources. Finally, we simulate the efficient resource scheduling capability in the spatial information network and empirically compare our approaches against two representative swarm intelligence baseline approaches and show that our approach has significant advantages in terms of performance and time consumption during resource scheduling. [ABSTRACT FROM AUTHOR]

Quantitative assessment of ecological vulnerability is of great significance for ecological protection and restoration in ecologically vulnerable regions. Here, the ecological vulnerability of the northern sand prevention belt (NSPB) of China was assessed using an ecological pressure–sensibility–resilience model from 2000 to 2015. Results showed that the ecological vulnerability index (EVI) displayed low values in the eastern part and high values in the western part of the study region. The EVI ranged from 0.29 to 1.32 in 2000, with the mean value of 0.88, whereas it averaged 0.78 in 2015, ranging from 0.21 to 1.26. Decreasing EVI from 2000 to 2015 indicated that the ecological status has been improved. Moreover, the area proportion of moderately, heavily, and extremely ecological vulnerability levels occupied approximately 87% in both 2000 and 2015, indicating a high ecological vulnerability level. Furthermore, the change in area proportion of different ecological vulnerability levels were associated with the change in the spatial distribution of vegetation coverage, indicating that eco-environmental protection projects were indeed effective. These findings indicated that differential strategies in different restoration zones should be adopted, especially in the western parts of the study region, and eco-environmental protection projects should be reinforced to improve the ecological restoration. [ABSTRACT FROM AUTHOR]

By only storing a unique copy of duplicate data possessed by different data owners, deduplication can significantly reduce storage cost, and hence is used broadly in public clouds. When combining with confidentiality, deduplication will become problematic as encryption performed by different data owners may differentiate identical data which may then become not deduplicable. The Message-Locked Encryption (MLE) is thus utilized to derive the same encryption key for the identical data, by which the encrypted data are still deduplicable after being encrypted by different data owners. As keys may be leaked over time, re-encrypting outsourced data is of paramount importance to ensure continuous confidentiality, which, however, has not been well addressed in the literature. In this paper, we design SEDER, a SEcure client-side Deduplication system enabling Efficient Re-encryption for cloud storage by (1) leveraging all-or-nothing transform (AONT), (2) designing a new delegated re-encryption (DRE), and (3) proposing a new proof of ownership scheme for encrypted cloud data (PoWC). Security analysis and experimental evaluation validate security and efficiency of SEDER, respectively. [ABSTRACT FROM AUTHOR]

Adventitious root (AR) formation was enhanced following the treatment of sugarcane microshoots with indole-3-butyric acid (IBA) and 1-naphthalene acetic acid (NAA) combined, suggesting that auxin is a positive regulator of sugarcane microshoot AR formation. The transcriptome profile identified 1737 and 1268 differentially expressed genes (DEGs) in the basal tissues (5 mm) of sugarcane microshoots treated with IBA+NAA compared to nontreated control on the 3rd and 7th days post-auxin or water treatment (days post-treatment—dpt), respectively. To understand the molecular changes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. This analysis showed that DEGs associated with the pathways were associated with plant hormone signaling, flavonoid and phenylpropanoid biosyntheses, cell cycle, and cell wall modification, and transcription factors could be involved in sugarcane microshoot AR formation. Furthermore, qRT–PCR analysis was used to validate the expression patterns of nine genes associated with root formation and growth, and the results were consistent with the RNA-seq results. Finally, a hypothetical hormonal regulatory working model of sugarcane microshoot AR formation is proposed. Our results provide valuable insights into the molecular processes associated with auxin-induced AR formation in sugarcane. [ABSTRACT FROM AUTHOR]

This paper is devoted to the study of the pricing of European options under a non-Gaussian model. This model follows a non-extensive statistical mechanics which can better describe the fractal characteristics of price movement in the financial market. Moreover, we present a simple but precise least-square method for approximation and obtain a closed-form solution of the price of European options. The advantages of this technique are illustrated by numerical simulation, which shows that the least-squares method is better compared with Borland's two methods in 2002 and 2004. [ABSTRACT FROM AUTHOR]

The surrounding rock control is a tough issue in the roadway with the swelling soft rock. The steel set is an important material for the control of swelling soft rock roadways. However, traditional steel sets failed to prevent the expansive pressure of the soft rock. Based on traditional steel sets, this paper developed a new steel set through both theoretical analysis and numerical simulation. The results showed that the new steel set was the set with the roof beam 1000 mm from the top of the set and the floor beam 400 mm from the bottom end of the set. The maximum deformations of the roof-floor and two sides of the ventilation roadway controlled by the best-improved set at the observation point were 147 mm and 108 mm, respectively. So, the best-improved set can effectively control the surrounding rock of the ventilation roadway. This provides an effective method for the surrounding rock control in extremely soft rock roadways. [ABSTRACT FROM AUTHOR]

The left-hand rolling-thread steel bolt has been proposed as a new bolt for controlling roadway surrounding rock. To explore the mechanism of a left-hand rolling-thread steel bolt in roadway surrounding rock control, its pretightening forces, tensile strengths, anchoring forces, and maximum working resistances were compared to normal right-hand full-thread steel bolts in the engineering context of the 1301 haulage roadway in the Daxing Coal Mine. Then, the left-hand threaded steel bolt was applied to the 1301 haulage roadway that the right-hand threaded steel bolt failed to control. The results indicated that due to the different effective tensile section area, the yield strength and tensile strength of the left-hand threaded steel bolt with the same material and diameter were more than 10% larger than those of the right-hand threaded steel bolt. Due to the different thread directions, the anchoring forces of the Φ18 and Φ20 left-hand threaded steel bolts were 46.2% and 33.3% greater than those of the right-hand threaded steel bolts, respectively. In the 1301 haulage roadway, the maximum pull-out force of the left-hand rolling-thread steel bolt with the same diameter was obviously greater than that of the right-hand full thread steel bolt. The displacements of the 1301 haulage roadway supported by the left-hand threaded steel bolt were not great. So, the left-hand threaded steel bolt can effectively control the surrounding rock in the 1301 haulage roadway. [ABSTRACT FROM AUTHOR]

Radio frequency (RF) stealth anti-sorting technology can improve the battlefield survival rate of radar and is one of the research hotspots in the radar field. In this study, the signal design principle of anti-sequential difference histogram (SDIF) sorting was explored for the main sorting algorithm of the SDIF. Furthermore, we designed a piecewise linear chaotic system with interval number parameterization based on random disturbance and proposed a method to modulate the repetition period of widely spaced signal pulses using a chaotic system. Then, considering the difficulty of the traditional signal processing method to measure the velocity of the highly random anti-sorting signals designed in this paper, we used compressed sensing (CS) technology to process the echoes of the signals to solve the velocity and distance of the detection targets. Finally, simulation verification was performed from the correctness of the signal design principle, the performance of the chaotic system, the anti-sorting performance of the designed signals and the recovery and reconstruction performance of the signals by CS. The results show that: (a) the signal design principle presented in this paper can guide the signal design correctly; (b) the performance of the piecewise linear chaotic system with interval number parameterization is better than that of the classical one-dimensional chaotic system; (c) the anti-sorting signal modulated by the chaotic system can achieve anti-SDIF sorting, and the anti-sorting signals designed in this paper can be processed to obtain the velocity and distance of the targets.

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.