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Automatic navigation based on dual-antenna real-time kinematic (RTK) positioning has been widely employed for unmanned agricultural machinery, whereas GNSS inevitably suffers from signal blocking and electromagnetic interference. In order to improve the reliability of an RTK-based navigation system in a GNSS-challenged environment, an integrated navigation system is preferred for autonomous navigation, which increases the complexity and cost of the navigation system. The information fusion of integrated navigation has been dominated by Kalman filter (KF) for several decades, but the KF cannot assimilate the known knowledge of the navigation context efficiently. In this paper, the geometric characteristics of the straight path and path-tracking error were employed to formulate the constraint measurement model, which suppresses the position error in the case of RTK-degraded scenarios. The pseudo-measurements were then imported into the KF framework, and the smoothed navigation state was generated as a byproduct, which improves the reliability of the RTK positioning without external sensors. The experiment result of the mobile vehicle automatic navigation indicates that the tracking error-constrained KF (EC-KF) outperforms the trajectory-constrained KF (TC-KF) and KF when the RTK system outputs a float or single-point position (SPP) solution. In the case where the duration of the SPP solution was 20 s, the positioning errors of the EC-KF and TC-KF were reduced by 38.50% and 24.04%, respectively, compared with those of the KF. [ABSTRACT FROM AUTHOR]

This paper develops a material-structure integrated design and optimization method based on a multiscale approach for the lightweight design of CFRP car doors. Initially, parametric modeling of RVE is implemented, and their elastic performance parameters are predicted using the homogenization theory based on thermal stress, exploring the impact of RVE parameters on composite material performance. Subsequently, a finite element model of the CFRP car door is constructed based on the principle of equal stiffness, and a parameter transfer across microscale, mesoscale, and macroscale levels is achieved through Python programming. Finally, the particle generation and updating strategies in the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm are improved, enabling the algorithm to directly solve multi-constraint and multi-objective optimization problems that include various composite material layup process constraints. Case study results demonstrate that under layup process constraints and car door stiffness requirements, plain weave, twill weave, and satin weave composite car doors achieve weight reductions of 15.85%, 14.54%, and 15.35%, respectively, compared to traditional metal doors, fulfilling the requirements for a lightweight design. This also provides guidance for the lightweight design of other vehicle body components. [ABSTRACT FROM AUTHOR]

Integrating global navigation satellite systems (GNSSs) with inertial navigation systems (INSs) has been widely recognized as an ideal solution for autonomous vehicle navigation. However, GNSSs suffer from disturbances and signal blocking inevitably, making the performance of GNSS/INSs degraded in the occurrence of measurement outliers. It has been proven that the sigma points-based Kalman filter (KF) performs better than an extended KF in cases where large prior uncertainty is present in the state estimation of a GNSS/INS. By modifying the sigma points directly, the resampling-free sigma point update framework (SUF) propagates more information excepting Gaussian moments of prescribed accuracy, based on which the resampling-free cubature Kalman filter (RCKF) was developed in our previous work. In order to enhance the adaptivity and robustness of the RCKF, the resampling-free SUF depending on dynamic prediction residue should be improved by suppressing the time-varying measurement outlier. In this paper, a robust observability-constrained RCKF (ROCRCKF) is proposed based on adaptive measurement noise covariance estimation and outlier detection, where the occurrence of measurement outliers is modelled by the Bernoulli variable and estimated with the state simultaneously. Experiments based on car-mounted GNSS/INSs are performed to verify the effectiveness of the ROCRCKF, and result indicates that the proposed algorithm outperforms the RCKF in the presence of measurement outliers, where the heading error and average root mean square error of the position are reduced from 1.96° and 6.38 m to 0.27° and 5.95 m, respectively. The ROCRCKF is robust against the measurement outliers and time-varying model uncertainty, making it suitable for the real-time implementation of GNSS/INSs in GNSS-challenged environments. [ABSTRACT FROM AUTHOR]

Ratooning rice is an essential rice-planting method. However, mechanical harvesting of the primary rice crop, while increasing efficiency, can negatively affect the yield of ratooning rice. Therefore, it is crucial to find ways to improve the grain yield of ratooning rice after the mechanical harvest of the primary rice. A two-year field experiment was conducted; the grain yield of ratooning rice was assessed by stubble righting after mechanical harvesting of primary rice. The study used two popular rice cultivars, YLiangyou911 and Kenliangyou801, as experimental materials. The experimental treatments included three groups: one without righting after rolling rice stubble (CK), another with mechanized righting after rolling rice stubble (T1), and a third one without rolling rice stubble by the machine (T2). The results of the study demonstrate that stubble righting after the mechanical harvest of primary rice (T1) had a substantial impact on the grain yield of ratooning rice. It led to grain yields similar to ratooning rice without mechanical rolling of the rice stubble (T2) and significantly outperformed the treatment without stubble righting after the mechanical harvest of primary rice (CK). The study observed significant effects of the year of the experiment (Y), the treatment applied (T), and the interaction between year and treatment (Y×T) on grain yield. Additionally, the treatment showed a significant influence on the yield components. Specifically, in 2021, the T1 and T2 treatments showed remarkable grain yield increases in YLiangyou911 by 107.41% and 147.97%, respectively, compared to CK. For Kenliangyou801 in 2021, the T1 and T2 treatments also resulted in notable improvements in grain yield by 45.85% and 114.26%, respectively. Similarly, in 2022, the grain yield increased by 6.99% for T1 and 23.87% for T2 in YLiangyou911, and by 77.23% for T1 and 187.13% for T2 in Kenliangyou801, compared to CK. The study also detected enhancements in several aspects, including biomass accumulation, solar radiation and photosynthetic characteristics, antioxidant response and nitrogen metabolism, and bud-regeneration capacity due to T1 and T2 treatments. Furthermore, correlation analysis was conducted to assess the relationship between grain yield and the investigated parameters. In conclusion, stubble righting after the mechanical harvest of primary rice resulted in significantly improved grain yield for ratooning rice. This improvement can be attributed to enhanced biomass accumulation, solar radiation and photosynthetic characteristics, antioxidant response and nitrogen metabolism, and increased bud-regeneration capacity. [ABSTRACT FROM AUTHOR]

In this study, an intelligent vehicle (IV) path tracking control method based on curvature optimisation is proposed to reduce the comprehensive performance conflict of the system. This system conflict is caused by the mutual restriction between the path tracking accuracy and the body stability during the movement of the intelligent automobile. First, the working principle of the new IV path tracking control algorithm is briefly introduced. Then, a three-degrees-of-freedom vehicle dynamics model and a preview error model considering vehicle roll are established. In addition, a path tracking control method based on curvature optimisation is designed to solve the deterioration of vehicle stability even when the path tracking accuracy of the IV is improved. Finally, the effectiveness of the IV path tracking control system is validated through simulations and the Hardware in the Loop (HIL) test with various conditions forms. Results clearly show that the optimisation amplitude of the IV lateral deviation is up to 84.10%, and the stability is improved by approximately 2% under the vx = 10 m/s and ρ = 0.15 m−1 condition; the optimisation amplitude of the lateral deviation is up to 66.80%, and the stability is improved by approximately 4% under the vx = 10 m/s and ρ = 0.2 m−1 condition; the body stability is improved by 20–30% under the vx = 15 m/s and ρ = 0.15 m−1 condition, and the boundary conditions of body stability are triggered. The curvature optimisation controller can effectively improve the tracking accuracy of the fuzzy sliding mode controller. The body stability constraint can also ensure the smooth running of the vehicle in the optimisation process. [ABSTRACT FROM AUTHOR]

The rapid development of hydrogen fuel cells has been paralleled by increased demand for lightweight type IV hydrogen storage vessels with high hydrogen storage density, which raises the performance requirements of internal plastic liners. An appropriate manufacturing process is important to improve the quality of polymer liners. In this paper, DSC, WAXD, a universal testing machine and a differential pressure gas permeameter were used to investigate the effect of the cooling rate of the rotational molding polyamide 11 on the thermal, crystallization, mechanical and barrier properties. The cooling rate is formulated according to the cooling rate that can be achieved in actual production. The results suggest that two PA11 liner materials initially exhibited two-dimensional (circular) growth under non-isothermal crystallization conditions and shifted to one-dimensional space growth due to spherulite collision and crowding during the secondary crystallization stage. The slower the cooling process, the greater the crystallinity of the specimen. The increase in crystallinity significantly improved the barrier properties of the two PA11 liner materials, and the gas permeability coefficient was 2-3-fold higher than at low crystallinity. Moreover, the tensile strength, the tensile modulus, the flexural strength, and the flexural modulus increased, and the elongation at break decreased as the crystallinity increased. [ABSTRACT FROM AUTHOR]

In this paper, glass fiber fabric reinforced polyphenylene sulfide composites were prepared by hot pressing. The effects of glass fibre modification and hot pressing temperature on the properties of the composites were investigated using a scanning electron microscope, infrared spectrometer, universal testing machine, and DIGEYE digital imaging colour measurement system. The results show that after the treatment with a silane coupling agent, the silane coupling agent was more uniformly distributed on the surface of the glass fibres, and the bonding effect between the glass fibre fabric and polyphenylene sulphide was significantly improved. The strength of the composites increased and then decreased with the increase of hot pressing temperature, and the surface colour of the composites became darker and darker. When the hot-pressing temperature is 310 °C, the mechanical properties of glass fabric-reinforced polyphenylene sulfide composites are at their best, the tensile strength reaches 51.9 MPa, and the bending strength reaches 78 MPa. [ABSTRACT FROM AUTHOR]

Glass fibre-reinforced polyphenylene sulphide composites were prepared by hot-pressing glass fibre fabrics and polyphenylene sulphide resins. The effects of different polyphenylene sulphide resin forms on the properties of the composites were investigated using scanning electron microscopy, dynamic mechanical analyser, pendulum impact tester and universal testing machine. The results showed that different polyphenylene sulphide resin forms had nearly no effect on the glass transition temperature of the composites, which are all located at about 100 °C. Compared with other polyphenylene sulphide composites, the bending strength of polyphenylene sulphide film composites was the highest, reaching 314.58 MPa, and the impact strength of polyphenylene sulphide particle composites was the highest, reaching 245.4 KJ/m2. The bending strength and impact strength were calculated using a standard fraction, and the highest standard fraction was obtained when the ratio of polyphenylene sulphide film to particle was 1:2. The impact strength and bending strength could be obtained. The impact strength reached 229.8 KJ/m2, and the bending strength reached 284.16 MPa. [ABSTRACT FROM AUTHOR]

This study optimized the laminate structure of a composite cylinder under the constraint of minimum layup thickness. Based on the progressive damage theory, a finite element model of the cylinder was established, and the NOL ring tensile test was used to verify the accuracy of the damage theory. The winding angle, the number of layers, and the helical/hoop ratio (the stacking sequence) were selected as the optimization factors, and the burst pressure value was used to evaluate the quality of the laminate structure. Then the orthogonal experiments were designed by RSM. Combined with FEA, the function model of the burst pressure of the gas cylinder and each optimization factor was established to obtain the optimal layering scheme, satisfying the minimum burst pressure. In addition, finite element analysis was used to verify the optimal scheme, demonstrating that the error of the burst pressure predicted by the quadratic model established by the response surface design was not more than 5%. This study provides a faster and more efficient optimization method for the optimization design of composite gas cylinder layers. [ABSTRACT FROM AUTHOR]

In this work, an in situ carbonization technique was employed using a dehydration reaction to construct an evaporator with a bilayer structure using polyvinyl alcohol (PVA) sponge as the raw material for solar-driven interfacial evaporation. Its top layer was uniformly covered with carbon species prepared from dehydration of the PVA sponge, which promoted light capture to warm water for steam generation. Meanwhile, its interconnected porous structure remained intact after carbonization of the PVA sponge and was accompanied by the presence of some oxygen-containing functional groups, which preserved its hydrophilicity. Furthermore, its bottom layer shared the micro-scale porous characteristic and favorable hydrophilicity of the pristine PVA sponge. The results illustrated that the prepared CS-3 evaporator was provided with remarkable evaporation performance, mirroring an evaporation rate of 1.38 kg m−2 h−1. Additionally, a stable evaporation rate at around 1.36 kg m−2 h−1 was observed during the 10-cycle test. More importantly, the water desalinated from seawater was drinkable, which met the World Health Organization (WHO) standard. Consequently, it can be concluded that the evaporator developed using in situ carbonization of PVA sponge possessed many development prospects in the field of seawater desalination. [ABSTRACT FROM AUTHOR]

Spray droplet size is the main factor affecting the deposition uniformity on a target crop. Studying the influence of multiple factors on the droplet size distribution as well as the evaluation method is of great significance for improving the utilization of pesticides. In this paper, volume median diameter (VMD) and relative span (RS) were selected to evaluate the droplet size distribution under different hollow cone nozzles, flow rates and spatial positions, and the quantitative models of VMD and RS were established based on machine learning methods. The results showed that support vector regression (SVR) had excellent results for VMD (Rc = 0.9974, Rp = 0.9929), while multi-layer perceptron (MLP) had the best effect for RS (Rc = 0.9504, Rp = 0.9537). The correlation coefficient of the prediction set is higher than 0.95, showing the excellent ability of machine learning on predicting the droplet size distribution. In addition, the visualization images of the droplet size distribution were obtained based on the optimal models, which provided intuitive guidance for realizing the uniform distribution of pesticide deposition. In conclusion, this study provides a novel and feasible method for quantitative evaluation of droplet size distribution and offers a theoretical basis for further determining appropriate operation parameters according to the optimal droplet size. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 infection has caused a global pandemic that has severely damaged both public health and the economy. The nucleocapsid protein of SARS-CoV-2 is multifunctional and plays an important role in ribonucleocapsid formation and viral genome replication. In order to elucidate its functions, interaction partners of the SARS-CoV-2 N protein in human cells were identified via affinity purification and mass spectrometry. We identified 160 cellular proteins as interaction partners of the SARS-CoV-2 N protein in HEK293T and/or Calu-3 cells. Functional analysis revealed strong enrichment for ribosome biogenesis and RNA-associated processes, including ribonucleoprotein complex biogenesis, ribosomal large and small subunits biogenesis, RNA binding, catalysis, translation and transcription. Proteins related to virus defence responses, including MOV10, EIF2AK2, TRIM25, G3BP1, ZC3HAV1 and ZCCHC3 were also identified in the N protein interactome. This study comprehensively profiled the viral–host interactome of the SARS-CoV-2 N protein in human cells, and the findings provide the basis for further studies on the pathogenesis and antiviral strategies for this emerging infection. [ABSTRACT FROM AUTHOR]

Filament-wound composite tubular structures are frequently used in transmission systems, pressure vessels, and sports equipment. In this study, the failure mechanism of composite tubes reinforced with different fibres under low-velocity impact (LVI) and the radial residual compression performance of the impacted composite tubes were investigated. Four fibres, including carbon fiber-T800, carbon fiber-T700, basalt fibre, and glass fibre, were used to fabricate the composite tubes by the winding process. The internal matrix/fibre interface of the composite tubes before the LVI and their failure mechanism after the LVI were investigated by scanning electric microscopy and X-ray micro-computed tomography, respectively. The results showed that the composite tubes mainly fractured through the delamination and fibre breakage damage under the impact of 15 J energy. Delamination and localized fibre breakage occur in the glass fibre-reinforced composite (GFRP) and basalt fibre-reinforced composite (BFRP) tubes when subjected to LVI. While fibre breakage damage occurs globally in the carbon fibre-reinforced composite (CFRP) tubes. The GFRP tube showed the best impact resistance among all the tubes investigated. The basalt fibre-reinforced composite (BFRP) tube exhibited the lowest structural impact resistance. The impact resistance of the CFRP-T700 and CFRP-T800 tube differed slightly. The radial residual compression strength (R-RCS) of the BFRP tube is not sensitive to the impact, while that of the GFRP tube is shown to be highly sensitive to the impact. [ABSTRACT FROM AUTHOR]

In the Fog Computer (FC), the process of data is prone to problems such as low data similarity and poor data tolerance. This paper proposes a hierarchical data job scheduling strategy Based on Intelligent Sensor-Cloud in Fog Computer (HDJS). HDJS dynamically adjusts the priority of the job to avoid job starvation and maximize the use of resources, uses the key frame to the resource occupied information, distributes the frame sequence to the unit, and then combines the intra frame distribution strategy to balance the load between the nodes. The experimental results show our proposed strategy may be possible to avoid the operation of hunger and resource fragmentation problems, make full use of the advantages of multi-core and multi-thread, improve system resource utilization, and shorten the execution time and response time. [ABSTRACT FROM AUTHOR]

Polylactic acid (PLA) is one of the most promising bio-based materials, but its inherent hydrophobicity limits its application. Although nanocellulose (NCC) is a desirable reinforcement for PLA, the poor interface compatibility between the two has been a challenge. In this work, hydroxyapatite (HAP) modified NCC was prepared, and the obtained NCC/HAP reinforcement was used to prepare PLA/NCC-HAP composites. Different ratios of NCC to HAP were studied to explore their effects on the mechanical and thermodynamic properties of the composites. When the ratio of NCC to HAP was 30/70, the tensile strength and tensile modulus of the composite film reached 45.6 MPa and 2.34 GPa, respectively. Thermogravimetric analysis results indicate that thermal stability of the composites was significantly improved compared with pure PLA, reaching 346.6 °C. The above revelations show that NCC/HAP significantly improved the interface compatibility with PLA matrix. [ABSTRACT FROM AUTHOR]

Efficient enhancement of the toughness of epoxy resins has been a bottleneck for expanding their suitability for advanced applications. Here, polysulfone (PSF) was adopted to toughen and modify the epoxy. The influences of PSF on the mechanical and thermal properties of the epoxy resin were systematically studied by optical microscopy, Fourier transform infrared spectrometer (FT-IR), differential scanning calorimetry (DSC), thermogravimetric analyzer (TG), dynamic mechanical thermal analyzer (DMA), mechanical tests and scanning electron microscope (SEM). The dissolution experimental results showed that PSF presents a good compatibility with the epoxy resin and could be well dissolved under controlled conditions. The introduction of PSF was found to promote the curing reaction of the epoxy resin without participating in the curing reaction and changing the curing mechanism as revealed by the FT-IR and DSC studies. The mechanical properties of PSF/epoxy resin blends showed that the fracture toughness and impact strength were significantly improved, which could be attributed to the bicontinuous phase structure of PSF/epoxy blends. Representative phase structures resulted from the reaction induced phase separation process were clearly observed in the PSF/epoxy blends during the curing process of epoxy resin, which presented dispersed particles, bicontinuous and phase inverted structures with the increase of the PSF content. Our work further confirmed that the thermal stability of the PSF/epoxy blends was slightly increased compared to that of the pure epoxy resin, mainly due to the good heat resistance of the PSF component. [ABSTRACT FROM AUTHOR]

The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy. [ABSTRACT FROM AUTHOR]

To satisfy the light weight requirements of vehicles owing to the aggravation of environmental pollution, carbon-fiber (CF)-reinforced epoxy composites have been chosen as a substitute for traditional metal counterparts. Since the current processing methods such as resin transfer molding (RTM) and compression molding (CM) have many limitations, an integrated and optimal molding method needs to be developed. Herein, we prepared high-performance composites by an optimized molding method, namely compression resin transfer molding (CRTM), which combines the traditional RTM and CM selectively and comprehensively. Differential scanning calorimetry (DSC) and rotational rheometry were performed to optimize the molding parameters of CRTM. In addition, metallurgical microscopy test and mechanical tests were performed to evaluate the applicability of CRTM. The experimental results showed that the composites prepared by CRTM displayed superior mechanical properties than those of the composites prepared by RTM and CM. The composite prepared by CRTM showed up to 42.9%, 41.2%, 77.3%, and 5.3% increases in tensile strength, bending strength, interlaminar shear strength, and volume fraction, respectively, of the composites prepared by RTM. Meanwhile, the porosity decreased by 45.2 %. [ABSTRACT FROM AUTHOR]

When the nodes in the network are deployed in the target area with an appropriate density, the effective aggregation and transmission of the data gathered in the monitoring area remain to be solved. The existing Compressed Sensing (CS) based on data aggregation schemes are accomplished in a centralized manner and the Sink node achieves the task of data aggregation. However, these existing schemes may suffer from load imbalance and coverage void issues. In order to address these problems, we propose a Compressed Sensing based on Fault-tolerant Correcting Data Aggregation (CS-FCDA) scheme to accurately reconstruct the compressed data. Therefore, the network communication overhead can be greatly reduced while maintaining the quality of the reconstructed data. Meanwhile, we adopt the node clustering mechanism to optimize and balance the network load. It is shown via simulation results, compared with other data aggregation schemes, that the proposed scheme shows obvious improvement in terms of the Fault-tolerant correcting capability and the network energy efficiency of the data reconstruction. [ABSTRACT FROM AUTHOR]

To satisfy the light weight requirements of vehicles owing to the aggravation of environmental pollution, carbon-fiber (CF)-reinforced epoxy composites have been chosen as a substitute for traditional metal counterparts. Since the current processing methods such as resin transfer molding (RTM) and compression molding (CM) have many limitations, an integrated and optimal molding method needs to be developed. Herein, we prepared high-performance composites by an optimized molding method, namely compression resin transfer molding (CRTM), which combines the traditional RTM and CM selectively and comprehensively. Differential scanning calorimetry (DSC) and rotational rheometry were performed to optimize the molding parameters of CRTM. In addition, metallurgical microscopy test and mechanical tests were performed to evaluate the applicability of CRTM. The experimental results showed that the composites prepared by CRTM displayed superior mechanical properties than those of the composites prepared by RTM and CM. The composite prepared by CRTM showed up to 42.9%, 41.2%, 77.3%, and 5.3% increases in tensile strength, bending strength, interlaminar shear strength, and volume fraction, respectively, of the composites prepared by RTM. Meanwhile, the porosity decreased by 45.2 %.