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Uncertainty exists about whether lowering systolic blood pressure to less than 120 mm Hg is superior to that of less than 140 mm Hg, particularly in patients with diabetes and patients with previous stroke.

Joining of large aspect ratio WC-based cemented carbide and Si3N4-based ceramic at 1650 °C was achieved via spark plasma sintering by using functionally graded material (FGM) as a bonding layer. The influence of FGM layer numbers on the bonding quality of the large aspect ratio WC-FGM-Si3N4composite materials was assessed based on thermal expansion coefficient and residual stress data. The microstructure analysis of the interface between adjacent layers revealed the formation of a structure with grain bidirectional anchoring, which promoted the enhancement of the bonding strength. High-strength joining of the large aspect ratio WC-FGM-Si3N4composite rods with the average shear strength of 210.5 MPa was successfully realised. Furthermore, the rod was ground into an end mill, and the obtained end mill connection strength fulfilled the stringent machining conditions for dry milling of nickel-based superalloys.

The orientation (including the caxis orientation and crystal direction parallel to rolling direction) evolution of grown recrystallization grains during annealing at 250 °C for 45–180 min in Mg–Zn-Gd alloy was characterized by quasi-in-situ electron backscatter diffraction method. An unusual grain orientation rotation during the process of static recrystallization grain growth, rather than common plastic deformation or recrystallization nucleation process, was observed. Due to the higher storage energy, the growth size in the early stage of annealing (1.41 μm) is larger than that in the late stage of annealing (0.73 μm) for most (∼76%) grains, and corresponding average c-axis rotation angles are 3.65° and 1.39°, respectively, indicating that the larger the increase in grain size, the greater the changing degree in grain orientation. It is speculated that the orientation rotation during grain growth process is mediated by the interaction between dislocations and grain boundaries. The results reported in the current paper can provide a new insight into the study on the relationship between preferential grain growth and non-basal texture formation in rare earth contained Mg alloys.

Nitrogen solid solution can effectively enhance the strength of steels, but its effect on grain boundary engineering and the corrosion mechanism of steels is still unclear and systematic investigation is needed. In this study, 316LN steel specimens with five nitrogen concentrations were melted and subjected to compression and annealing. The grain boundary character distribution was investigated by electron backscatter diffraction. The corrosion behavior was investigated by the electrochemical polarization curves, electrical impedance spectroscopy, and X-ray photoelectron spectroscopy. The results showed that nitrogen promotes the formation of low-Σ boundaries when the pre-strain is not above 10%. The polarization resistance increases with increasing nitrogen content. The quantitative relationship between the nitrogen content and the pitting potential was obtained. Nitrogen favors the formation of oxides, hydroxides, and NH3/NH4+on the passivated surface. The effect of planar slip on grain boundary engineering and the influence of NH4+on the corrosion resistance are discussed.

This article investigates the state interval estimation problem for discrete-time linear time-varying descriptor systems subject to unknown but bounded system uncertainties. We propose a zonotope-based interval estimation method in an optimization framework. First, we present a novel zonotope-based interval estimator structure, in which the estimated interval bounds of each state component have design parameters independent of those of the other state components. Then, the widths of the jointly estimated intervals enclosing every state component are simultaneously minimized by solving parallel $L_{1}$ optimization problems via linear programming. Finally, a simulation study shows the effectiveness and higher accuracy of the proposed method compared with existing methods.

This article proposes a two-step interval estimation method for discrete-time Takagi–Sugeno fuzzy nonlinear systems with parameter uncertainties. First, a novel observer structure without redundant parameters is proposed to obtain point-valued estimation for the considered system. Compared with the $T$–$N$–$L$ observer structure recently presented in the literature, the proposed observer structure is more concise and can simplify the design process. To improve the estimation accuracy, an $H_\infty$ design method that can simultaneously optimize all design parameters by solving linear matrix inequalities is proposed to design the proposed observer. Second, interval estimation is achieved by zonotopic analysis on the error dynamics of the designed observer. Comparison studies show that the proposed method not only has broader application scopes but also can obtain more accurate estimation results than a state-of-the-art interval observer design method. Moreover, the proposed method is applied to a missile control system to estimate the intervals of the attack angle and pitch rate.

Developing effective irrigation and drainage strategies to improve the quality of saline-alkali soil is vital for enhancing agricultural production and increasing economic returns. In this study, we explored how irrigation and drainage modes (flood irrigation, drip irrigation, and sub-surface pipe drainage under drip irrigation) improve the saline-alkali soil in Xinjiang, China. We aimed to study the transport characteristics of soil water and salt under different irrigation and drainage modes, and analyze the effects of the combination of irrigation and drainage on soil salt leaching, as well as its impacts on the growth of oil sunflower. Our results show that sub-surface pipe drainage under drip irrigation significantly reduced the soil salt content and soil water content at the 0–200 cm soil depth. Under sub-surface pipe drainage combined with drip irrigation, the mean soil salt content was reduced to below 10 g/kg after the second irrigation, and the soil salt content decreased as sub-surface pipe distance decreased. The mean soil salt content of flood irrigation exceeded 25 g/kg, and the mean soil desalination efficiency was 3.28%, which was lower than that of drip irrigation. The mean soil desalination rate under drip irrigation and sub-surface pipe drainage under drip irrigation was 19.30% and 58.12%, respectively. After sub-surface drainage regulation under drip irrigation, the germination percentage of oil sunflower seedlings was increased to more than 50%, which further confirmed that combined drip irrigation and sub-surface pipe drainage is very effective in improving the quality of saline-alkali soil and increasing the productivity of agricultural crops.

In this study, powder mixtures containing (Ti, W)C additions (10, 20, 30 and 40 wt%) were prepared and then consolidated at 1200, 1250, 1300 and 1350 °C by spark plasma sintering. The effect of (Ti, W)C additions on the microstructure and mechanical properties of ultrafine WC–Co materials was investigated. The results demonstrate that the (Ti, W)C not only retards the sintering densification but also increases the porosity of sintered samples. The increasing sintering temperature is beneficial to the densification but results in the grain coarsening and the dissolution of W in (Ti, W)C. Moreover, there are no (Ti, W)C grains with obvious core/rim structure in the microstructure. With the (Ti, W)C increasing from 10 to 20 wt%, the hardness increases and fracture toughness changes hardly. However, the hardness and fracture toughness decrease slightly as the (Ti, W)C further increases. The transgranular fracture of (Ti, W)C phases is responsible for the slight reduction in fracture toughness. The sample with 20 wt% (Ti, W)C has high hardness and fracture toughness (HV: 21.3 GPa, KIC: 9.8 MPa m1/2).

Named entity disambiguation (NED) finds the specific meaning of an entity mention in a particular context and links it to a target entity. With the emergence of multimedia, the modalities of content on the Internet have become more diverse, which poses difficulties for traditional NED, and the vast amounts of information make it impossible to manually label every kind of ambiguous data to train a practical NED model. In response to this situation, we present MMGraph, which uses multimodal graph convolution to aggregate visual and contextual language information for accurate entity disambiguation for short texts, and a self-supervised simple triplet network (SimTri) that can learn useful representations in multimodal unlabeled data to enhance the effectiveness of NED models. We evaluated these approaches on a new dataset, MMFi, which contains multimodal supervised data and large amounts of unlabeled data. Our experiments confirm the state-of-the-art performance of MMGraph on two widely used benchmarks and MMFi. SimTri further improves the performance of NED methods. The dataset and code are available at https://github.com/LanceZPF/NNED_MMGraph.

Background and aimsDeregulation of RNA N6-methyladenosine (m6A) modification in intestinal epithelial cells (IECs) influences intestinal immune cells and leads to intestinal inflammation. We studied the function of fat mass-and obesity-associated protein (FTO), one of the m6A demethylases, in patients with ulcerative colitis (UC).MethodsWe analysed colon tissues of Ftoflox/flox; Villin-cre mice and their Ftoflox/floxlittermates with dextran sulfate sodium (DSS) using real-time PCR and 16s rRNA sequencing. RNA and methylated RNA immunoprecipitation sequencing were used to analyse immunocytes and IECs. Macrophages were treated with conditioned medium of FTO-knockdown MODE-K cells or sphingosine-1-phosphate (S1P) and analysed for gene expression. Liquid chromatograph mass spectrometry identified C16-ceramide.ResultsFTO downregulation was identified in our in-house cohort and external cohorts of UC patients. Dysbiosis of gut microbiota, increased infiltration of proinflammatory macrophages, and enhanced differentiation of Th17 cells were observed in Ftoflox/flox;Villin-cre mice under DSS treatment. FTO deficiency resulted in an increase in m6A modification and a decrease in mRNA stability of CerS6, the gene encoding ceramide synthetase, leading to the downregulation of CerS6 and the accumulation of S1P in IECs. Subsequentially, the secretion of S1P by IECs triggered proinflammatory macrophages to secrete serum amyloid A protein 1/3, ultimately inducing Th17 cell differentiation. In addition, through bioinformatic analysis and experimental validation, we identified UC patients with lower FTO expression might respond better to vedolizumab treatment.ConclusionsFTO downregulation promoted UC by decreasing CerS6 expression, leading to increased S1P accumulation in IECs and aggravating colitis via m6A-dependent mechanisms. Lower FTO expression in UC patients may enhance their response to vedolizumab treatment.

Efficient feature extraction is vital for assessing classification performance in deep learning (DL) networks. While attention mechanisms enhance feature extraction, their fixed structures limit performance across diverse tasks. In this article, a mobile switched attention network (MSAN) is proposed for the classification of surface defects on co-fired piezoelectric actuators (CPEAs), which employ weakly supervised training with only image-level labels. The MSAN utilizes a novel training strategy with a switching attention block (SAB), allowing dynamic adjustments to the attention block’s structure in real time using switch cells. By employing this adaptive approach, the focus on key feature information is enhanced, and the model parameters are optimized, thereby significantly improving the feature extraction ability. Meanwhile, a weight-sharing testing strategy is implemented, allowing the simple configuration network to utilize the optimal parameters for accurate decision making. Additionally, a data cleaning module (DCM) and a visualization method are introduced to mitigate external environmental noise during network training and increase network interpretability, respectively. Experiments are conducted to validate the effectiveness of the proposed MSAN.

Abstract: The arsenic contamination accident in Yangzonghai Lake, Yunnan has been of wide concern. In order to investigate the arsenic distribution and concentration trends after the accident, samples including lake water, sediments, soil, aquatic organisms and crops were collected in November 2008, as well as in February, May and September 2009. The average arsenic concentrations (arithmetic average) in lake water in the four sampling events were 176.9, 147.3, 159.3, and 161-1 μg/L, while those in the sediments were 32.87, 62.41, 62.99, and 46.96 μg/g, respectively. The highest content of total arsenic in soil in the vicinity of Yangzonghai was 23.33 μg/g, which was below the limits of the relevant national standard. The total arsenic levels in most aquatic plants were in the range of 100–200 μg/g, with Vallisneria natans (Lour.) Hara having the highest concentration of ∼300 μg/g. The arsenic levels of fish and shrimps were in the range of 1.52–11.4 μg/g (dry weight).

Ultrathin foils are used in multiple fields, including aerospace, and precision instrument design. In this paper, CoCrNi medium-entropy alloy (MEA) ultrathin foils with terminal thicknesses of 77 μm were prepared by accumulative cold rolling at room temperature. The quasi-static tensile properties of the rolled ultrathin foils were tested. The influence of the reduction ratio and thickness values on their mechanical properties was studied through EBSD and TEM. The results showed that the CoCrNi MEA ultrathin foils exhibited excellent tensile performance when the thickness reached 160 μm, in which the tensile strength reached 1.69 GPa at a tensile elongation of 7 %. Microstructure characterization revealed that the dominant strengthening mechanism of the CoCrNi ultrathin foils were composed of grain boundary and dislocation strengthening. Specifically, when the thickness exceeded 160 μm, enhanced dislocation and grain size strengthening cause ' work hardening ', and the strength gradually increased with decreasing thickness. When the thickness was 160 μm, the strengthening effect produced by dislocation banding, twinning, and multistage twinning delivery significantly influenced the mechanical properties of the foils. When the thickness was less than 160 μm, this process mainly occurred due to the interactions of dislocation proliferation and annihilation in the grain, causing the strength to decrease gradually with decreasing thickness, thereby resulting in ' work softening '.

Despite the intensive research in room-temperature phosphorescent (RTP) polymers, the synthesis of RTP polymers with well-defined macromolecular structures and multiple functions remains a challenge. Herein, reversible deactivation radical polymerization was demonstrated to offer a gradient copolymer (GCP) architecture with controlled heterogeneities, which combines hard segment and flexible segment. The GCPs would self-assemble into a multiphase nanostructure, featuring tunable stretchability, excellent RTP performance, and intrinsic healability without compromising light emission under stretching. The mechanical performance is tunable on demand with elongation at break ranging from 5.0% to 221.7% and Young’s modulus ranging from 0.5 to 225.0 MPa.

In this work, an actuator fault detection problem for discrete-time Takagi–Sugeno fuzzy systems is tackled in a bounded error context where both state disturbances and measurement noise are assumed to be unknown but bounded with known bounds. First, a peak-to-peak performance synthesis method is applied to design a robust residual generator against the considered process disturbances and measurement noise. Meanwhile, an improved zonotopic approach is proposed to compute tight adaptive thresholds for residual evaluation. Then, a reliable set-membership fault detection strategy with the aid of generated residual signals and adaptive thresholds is introduced. Finally, the viability of the proposed method is demonstrated via a numerical simulation. Then, an experimentation on a 3-D Crane system is performed to show its practicability.

This article studies the problem of sensor attack detection for a class of cyber-physical systems with bounded perturbations. A novel attack detection method is proposed based on zonotopic reachability analysis. A false data injection attack is detected if there is no intersection between the predicted state set and the measurement state set. These sets are online calculated via zonotopic segments minimization. Two approaches, namely, projection and polytopic conversion, are presented to check the intersection situation. The detection performance is quantified using a stealthy attack set and the corresponding state estimation error set. Further, we consider replay attacks. To detect a replay attack, a watermark signal-based active detection mechanism is introduced. Numerical simulations are conducted to demonstrate the validity of the proposed method.

Compared with the progress made on human activity classification, much less success has been achieved on human interaction understanding (HIU). Apart from the latter task is much more challenging, the main causation is that recent approaches learn human interactive relations via shallow graphical representations, which are inadequate to model complicated human interactive-relations. This paper proposes a deep consistency-aware framework aiming at tackling the grouping and labelling inconsistencies in HIU. This framework consists of three components, including a backbone CNN to extract image features, a factor graph network to implicitly learn higher-order consistencies among labelling and grouping variables, and a consistency-aware reasoning module to explicitly enforcing consistencies. The last module is inspired by our key observation that the consistency-aware reasoning bias can be embedded into an energy function or a particular loss function, minimizing which delivers consistent predictions. An efficient mean-field inference algorithm is proposed, such that all modules of our network could be trained in an end-to-end fashion. Experimental results demonstrate that the two proposed consistency-learning modules complement each other, and both make considerable contributions in achieving leading performance on three benchmarks of HIU. The effectiveness of the proposed approach is further validated by experiments on detecting human-object interactions.

This article studies set-membership estimation for discrete-time linear time-varying systems with unknown-but-bounded uncertainties. An ellipsoidal set-membership filtering method with a new estimator is proposed. Based on the S-procedure, the proposed set-membership filtering is formulated as an optimization problem in terms of linear matrix inequalities. Moreover, it is shown that the optimal ellipsoids estimated by two existing set-membership filtering approaches are equivalent to the optimal estimation results obtained by two special cases of the proposed method, respectively. The proposed estimator has more design parameters which can be effectively optimized to improve the estimation accuracy. Simulation results are given to show the performance of the proposed method.

Hastelloy G30 is a typical representative of Ni–Cr–Fe–Mo–Cu alloys, which have excellent corrosion resistance and mechanical properties. High alloying-element content induces a risk of intermetallic precipitation, which is poorly eliminated in steel/nickel bimetallic composite manufactured by hot forming or welding. In this study, aged material was observed using transmission electron microscopy, electron backscatter diffraction, and scanning electron microscopy. The results show that the precipitates formed in Hastelloy G30 after aging at 800 °C comprised Cr- and Mo-rich σ phase. More than 95% of Σ1 and Σ3 boundaries were free from σ phase, and about half of the other low-Σ boundaries were immune to the formation of σ phase. All Σ9, Σ27, and random high-angle grain boundaries exhibited low intergranular precipitation resistance of approximately 5%–10%. The (301) planes of the σ phase and the (−220) planes of the matrix showed semicoherent lattice matching. Higher grain-boundary energy and serrated grain boundaries provided opportunities for σ phase precipitation to occur.

In this study, consensus issue for general linear continuous-time multiagent systems (MASs) in a directed network is addressed. Suppose that the neighbors’ transmitted information is impacted by a communication delay, explicit consensus criteria are, respectively, obtained for both known delay and unknown delay cases. Especially, a new protocol applying the delay information is proposed if the delay is available. Furthermore, it is proved that the influence of delay can be eliminated thoroughly if the agent dynamic is at most critically unstable or the network topology satisfies the presented criteria. Finally, two simulation paradigms are performed to clarify the practicality of the newly developed methods.

The graphite/lithium metal hybrid anode shows great potential for achieving high-specific-energy lithium batteries. Despite the “dead lithium” problem caused by repeated stripping and deposition of Li component based on a conversion reaction, the degradation mechanism, based on intercalation reaction, of graphite in a hybrid anode is generally ignored. In this contribution, through in situ X-ray diffraction and in situ Raman analysis, we reveal that hysteresis and the mixed-phase state of graphite during deintercalation play a critical role in hybrid battery degradation. On the other hand, we successfully mitigated graphite degradation and increased the reversible capacity of the hybrid anode by introducing an inorganic-rich solid electrolyte interface. Remarkably, the hybrid anode (30% higher specific capacity compared to graphite) exhibits an average coulombic efficiency of 99.11% and retains 96.13% of initial capacity over 120 cycles. This work sheds new light on the advancement of high-specific-energy lithium secondary batteries.

Graphic abstract: The structure, dielectric and magnetoelectric effect.

The effects of confinement and hydrodynamic interactions on single-chain diffusion behaviors are studied by using a combination of molecular dynamics and multiparticle collision dynamics simulations. For polymers in free space, the simulation results showed that the diffusion coefficient D∞for long chains scales with the chain length Nas D∞∼ N–ν(ν = 0.588), consistent with the Zimm dynamics, but it deviates from the Zimm dynamics for short chains. For polymers confined in channels with width H, the diffusion coefficient is found to follow two different scaling relations. The observed behaviors could be understood by introducing a microscopic hydrodynamic length ξh, below which the overall effect of hydrodynamic interactions becomes less important. For a confined chain, the diffusion behavior exhibits a crossover from Zimm (nondraining) to Rouse (free draining) dynamics as the channel size Hdecreases. When His larger than ξh, the confinement experienced by the polymer chain is weak and the diffusion coefficient scales as D∼ H0.7, in accordance with the prediction of blob theory; when His smaller than ξh, Dbecomes independent of H, implying a free draining condition. A general analytical expression of Dis derived by extending the partially permeable sphere model to the blob scale, which gives a quantitative description of the transition from Zimm to Rouse dynamics as Hdecreases.

Graphical abstract:

This article investigates the adaptive event-triggered output-feedback control problem for a class of switched stochastic nonlinear systems with actuator faults. In the existing works, the developed results on adaptive control for switched stochastic nonlinear systems are almost based on the average dwell-time method, and how to construct a desired adaptive controller in the frame of the mode-dependent average dwell time (MDADT) remains a control dilemma. By presenting a general adaptive control rule based on the MDADT, this article implements the adaptive output-feedback control for the switched stochastic system under interest. In the process of controller design, fuzzy-logic systems, a flexible approximator, are utilized to approximate the unknown nonlinear functions. The dynamic surface design approach is employed to avoid taking derivatives of the constructed virtual controls to decrease the difficulty of complex calculation greatly. Meanwhile, a switched observer is designed to estimate the unknown states. In the frame of backstepping design, an event-triggered-based adaptive output-feedback controller is constructed such that all signals existing in the closed-loop system are ultimately bounded under a class of switching signals with MDADT property. Finally, the simulation results show the validity of the proposed control strategy.

This article studies the security synthesis of cyber–physical systems subject to stealthy attacks via zonotopic set theory. The set is used to quantify the effect of potential stealthy attacks on systems. Control performance and security level are characterized using $L_{\infty }$ performance index and the radius of the attack-induced state set, respectively. Sufficient design conditions are given to optimize the security while guaranteeing a prescribed level of control performance. Simulation examples are conducted to demonstrate the effectiveness of the proposed method.

This work is concerned with the problem of replay attack detection for unmanned surface vehicles subject to bounded perturbations. A novel zonotopic noisy control input is designed to reveal the signature of replay attacks. The resulting performances of control loss and detection increased are characterized as the size of a steady-state set and a measurement deviation set, respectively. Sufficient conditions for optimizing the detection while guaranteeing a prescribed level of control performance are formulated as a Lyapunov equation. Simulation results demonstrate the validity and viability of the proposed method.

This paper proposes a two-step distributed interval estimation method for continuous-time linear time-invariant (LTI) systems subject to unknown but bounded disturbance and measurement noise. First, a network of local observers is designed to obtain point-wise estimation. Second, interval estimation is obtained based on the point-wise estimation and peak-to-peak analysis. The conditions of the observer design and the peak-to-peak analysis are formulated as linear matrix inequalities, which can be solved efficiently. Compared with the distributed interval observers designed using the monotone system theory, the proposed method has less restrictive design conditions and hence broader application scopes. Moreover, the parameter matrices in the proposed method can be optimized to obtain tight interval estimation. A numerical simulation is given to illustrate the performance of the proposed method.

This study considers the problem of interval estimation for event-triggered 2-D systems in Fornasini–Marchesini local state-space (FMLSS) model. In such systems, the general hypothesis for practical applications is that exogenous disturbances and measurement noise are unknown but bounded. First, an observer design criterion is deduced from the defined zonotopic radius and weighted radius of the FMLSS model. Subsequently, to economize the restricted communication resources, an event-driven data transmission strategy is employed for the observer. Then, a sufficient criterion is established to guarantee the $\mathcal {L}_\infty$ performance for the considered 2-D FMLSS system with the event-triggered scheme. From the obtained observer, the estimation interval of the 2-D system is derived by using the zonotopic state estimation approach. Finally, the validity is confirmed by simulations.

3D visualization platform, which can display the status of a satellite, is significantly important for telemetry data analysis. This paper presents a 3D visualization platform developed using CesiumJS for the web. The platform is developed for the visualization of the satellites of Yinhe Hangtian Corporation. To ensure the effectiveness and validity of the platform, its prototype is developed and verified by numerical simulations of three missions, which are initial rate damping, sun-pointing control, and earth-pointing control. After verifying the validity of the platform, it is connected to the telemetry database and is further developed by adding new capabilities such as the display of movable components (such as solar panels and the antennas). This platform now is applying to the visualization of the 02P satellites launched by the Yinhe Hangtian Corporation. The platform, which is able to display the satellite's orbit, attitude, and the communication area covered by the QV and KA band, greatly facilitate the analysis of the 02P satellites.

This paper presents a functional interval estimation method for continuous-time systems subject to disturbances and noise. First, a robust functional observer is synthesised to attenuate the effects of uncertainties. Then, based on interval analysis, an interval-based method is proposed to achieve tight functional interval estimation. The proposed method can provide accurate functional interval estimation results for continuous-time systems without using the stringent cooperativity condition and the traditionally required condition on the time derivative of the measurement noise. Simulation results are given to illustrate the effectiveness and superiority of the proposed method.

This paper studies the problem of velocity sensor fault detection for Autonomous Underwater Vehicles. A novel fault detection method is proposed based on zonotopes. The fault is detected based on the check of the intersection between the prediction state set and the measurement state set. The performance of the proposed method is evaluated via a minimum detectable fault set. Numerical simulation is conducted to demonstrate the validity and viability of the proposed method.

Maize rough dwarf disease (MRDD), caused by maize rough dwarf virus (MRDV) or rice black-streaked dwarf virus (RBSDV), seriously threatens worldwide production of all major cereal crops, including maize, rice, wheat and barley. Here we report fine mapping and cloning of a previously reported major quantitative trait locus (QTL) (qMrdd2) for RBSDV resistance in maize. Subsequently, we show that qMrdd2encodes a G2-like transcription factor named ZmGLK36that promotes resistance to RBSDV by enhancing jasmonic acid (JA) biosynthesis and JA-mediated defence response. We identify a 26-bp indel located in the 5′ UTR of ZmGLK36that contributes to differential expression and resistance to RBSDV in maize inbred lines. Moreover, we show that ZmDBF2, an AP2/EREBP family transcription factor, directly binds to the 26-bp indel and represses ZmGLK36expression. We further demonstrate that ZmGLK36plays a conserved role in conferring resistance to RBSDV in rice and wheat using transgenic or marker-assisted breeding approaches. Our results provide insights into the molecular mechanisms of RBSDV resistance and effective strategies to breed RBSDV-resistant cereal crops.

To study the effects of different stress gradient on rockburst hazards, a novel experimental technique was proposed and a series of tests under different stress gradient paths were conducted on specimens (400 mm × 600 mm × 1000 mm) by using a true-triaxial gradient and hydraulic-pneumatic combined test device. The damage phenomena, force characteristics and acoustic emission (AE) signals of the specimen during rockbursts were systematically analyzed. The experimental results indicated that different stress gradient distributions not only affect the failure mechanism of the specimen, but also affect the energy conversion characteristics. With the stress gradient increasing from 0 to 6, the index rdecreasing from 0.93 to 0.37, and the power law growth characteristics of the energy acceleration tends to be obvious. The energy released after rockburst accounts for 31.1%, 41%, 77.7%, and 87.5% of the total energy, respectively, which is an important reason for the severe damage tendency of rockburst. Rockburst intensity can be judged according to the stress/strength ratio corresponding to the inflection point of the AE energy fitting curve under different stress gradients, which can be used as an important precursor of rockburst.

Current pandemic has caused the medical system to operate under high load. To relieve it, robots with high autonomy can be used to effectively execute contactless operations in hospitals and reduce cross-infection between medical staff and patients. Although semantic Simultaneous Localization and Mapping (SLAM) technology can improve the autonomy of robots, semantic object association is still a problem that is worthy of being studied. The key to solving this problem is to correctly associate multiple object measurements of one object landmark by using semantic information, and to refine the pose of object landmark in real time. To this end, we propose a hierarchical object association strategy and a pose-refinement approach. The former one consists of two levels, i.e., a short-term object association and a global one. In the first level, we employ the multiple-object-tracking for short-term object association, through which the incorrect association among objects whose locations are close and appearances are similar can be avoided. Moreover, the short-term object association can provide more abundant object appearance and more robust estimation of object pose for the global object association in the second level. To refine the object pose in the map, we develop an approach to choose the optimal object pose from all object measurements associated with an object landmark. The proposed method is comprehensively evaluated on seven simulated hospital sequences, a real hospital environment and the KITTI dataset. Experimental results show that our method has an obviously improvement in terms of robustness and accuracy for the object association and the trajectory estimation in the semantic SLAM.

This article proposes an intervalestimation method for discrete-time Lipschitz nonlinear systems via observer design and ellipsoidal analysis. A robust observer with novel structure is presented, which provides more degrees of design freedom and can be applied to enhance the interval estimation performance. To handle the nonlinear term in Lipschitz systems, we use the reformulated Lipschitz property to transform the nonlinear error dynamics into a linear parameter-varying form. After the transformation, the robustness performance of the proposed observer is characterized with the aid of peak-to-peak index. Furthermore, the comprehensive interval estimation results are obtained by using the peak-to-peak performance and the ellipsoidal analysis. Numerical simulation results are conducted to demonstrate the viability and validity of the presented method.

Affected by reservoir heterogeneity, developed natural fractures, and bedding fractures, the fracturing pressure curves in fracturing of shale gas horizontal wells present complex shapes. A large amount of information contained in the fracturing curves is still not fully excavated. Based on the theory of shale gas fracture network fracturing, the calculation model of bottom hole net pressure is established by integrating the real-time data such as casing pressure, pump rate, and proppant concentration. Net pressure slope and net pressure index are constructed as key parameters, and the net pressure curve is divided dynamically to describe the mechanical conditions corresponding to the fracture propagation behavior during the fracturing process. Six fracture propagation modes were identified, including fracture network propagation, fracture propagation blockage, normal fracture propagation, fracture propagation long bedding, fracture height growth, and rapid fluid filtration, and then the operation pressure curve diagnosis and identification method were formed for shale gas fracture network fracturing in horizontal wells. The shortcomings of conventional operation curve diagnosis and identification methods are abandoned and the fracture network complexity index is presented. The higher index indicates more time of fracture network propagation and fracture propagation along bedding and the better reservoir stimulation effect. The model is applied to shale gas wells in the southeastern margin of Sichuan Basin, and the average fracture network complexity index of a single well is 0.3, which is in good agreement with the microseismic monitoring results. This proves the good reliability of the method developed. The method is helpful to improve the potential and level of fracturing stimulation of shale reservoirs and is of great significance for improving the post-fracturing evaluation technology of fracture network and guiding the real-time dynamic adjustment of field fracturing operations.

The CNT-CoN-VNmodified separator can promote the anchoring and conversion kinetics of polysulfides as well as the diffusion of Li ions, leading to enhanced electrochemical performance of Li-S batteries.

Graphical abstract: The effect of sintering temperature on the multiferroic properties of hexagonal barium ferrite (BaM) ceramics was studied. The ferroelectric and magnetic hysteresis loops of the ceramics indicate the room temperature multiferroic properties of the prepared ceramics. The effect of leakage current on ferroelectric properties of ceramics was also studied. It lays a foundation for the study of single-phase multiferroic materials at room temperature.

This study was conducted to investigate the effects of glycerol monolaurate (GML) on lipopolysaccharide (LPS)-induced immunological stress and intestinal mucosal injury in broilers and its underlying mechanisms. A total of 144 one-d-old Arbor Acres broilers were allocated to a 2 × 2 factorial arrangement involving dietary treatment (0 or 1,200 mg/kg dietary GML) and LPS challenge (injected with saline or Escherichia coliLPS on d 16, 18, and 20). Samples were collected on d 21. The results revealed that dietary GML augmented serum immunoglobulin A (P = 0.009) and immunoglobulin G (P < 0.001) levels in challenged birds. Dietary GML normalized LPS-induced variations in serum interleukin-6, interferon-gamma, and LPS levels (P < 0.05), jejunal villus height (P = 0.030), and gene expression of interleukin-6, macrophage inflammatory protein-3 alpha, Toll-like receptor 4, nuclear factor kappa-B, caspase-1, tight junction proteins, adenosine monophosphate-activated protein kinase alpha 1 (AMPKα1), nuclear factor-erythroid 2-related factor 2 (Nrf2), and superoxide dismutase-1 (P < 0.05). GML supplementation ameliorated LPS-induced peroxidation by reducing malondialdehyde content and increasing antioxidant enzyme activity (P < 0.05). Dietary GML enhanced the abundances of Anaerostipes, Pseudoflavonifractor, and Gordonibacterand reduced the proportion of Phascolarctobacteriumin challenged birds. Dietary GML was positively correlated with alterations in antioxidant enzyme activities and AMPKα1, Nrf2, and zonula occludens-1 expressions. The genera Anaerostipes, Lachnospira, Gordonibacter, Lachnospira, Marvinbryantia, Peptococcus, and Pseudoflavonifractorwere linked to attenuated inflammation and improved antioxidant capacity of challenged birds. In conclusion, dietary GML alleviated LPS-induced immunological stress and intestinal injury of broilers by suppressing inflammation and oxidative stress. Dietary GML regulated cecal microbiota and activated the AMPK/Nrf2 pathway in LPS-challenged broilers.

Set-membership state estimation problem for a certain class of discrete-time nonlinear systems is tackled in this work. First, this problem is formulated as a reachability analysis problem. Then, to avoid the wrapping effect, explicit expression of the general solution of this class of systems is used to design new set-valued state estimation schemes. Moreover, for practical considerations, two periodically re-initialized algorithms based on both interval analysis and zonotope computation are introduced. The merit of the proposed approach is illustrated on a numerical example and its performance is compared to that of other methods borrowed from the literature.

The fouling and flashing of line insulators often cause serious damage to transmission lines and makes subsequent maintenance difficult, so being able to assess the fouling status of insulators in real time is an important step in achieving life-cycle control of insulators. For the purpose of predicting the actual operating condition of insulators, this paper uses line insulators as the object of study, takes leakage current, ambient relative humidity and ambient temperature as evaluation parameters, and selects the RBF neural network model, which can reflect the non-linear influence of multiple factors, as the method to assess the degree of insulator fouling, and establishes a real-time data-based operating insulator fouling assessment model. Training data and the model structure are important for the accuracy of the fouling assessment model. Therefore, 440 sets of simulated data are selected as the training data for the model simulation, and the model structure with the best fit to the training results is compared by changing the model parameters. This paper presents a real-time fouling assessment model for transmission line insulators of 110–500 kV voltage level, which provides the basic data for the subsequent whole life cycle control of insulators.

The precipitation behavior of second phases and mechanical property of Fe–13.5Cr–4.7Al–2.1Mo–0.5Nb–0.8Ta–0.2Zr (wt.%) alloy was investigated in the present study. Alloy ingots were fabricated by vacuum arc melting and multi-pass hot rolling, then solid-solutionized at 1473 K for 2 h and aged at 1073 K for 0–24 h. In the initial aging process, the precipitated phase were mainly composed of spherical Laves Fe2M (M = Nb, Ta, Zr) and Fe23Zr6particles. With increasing the aging time, the morphology of Laves phase particles changed gradually from the spherical shape to short-rod shape, and then to granular shape. While the Fe23Zr6particles still remain spherical during the whole aging process. It is closely related to the lattice misfit between precipitated phase and the BCC matrix, in which the lattice misfit of ε = 1.3% between Fe2M and BCC is remarkably larger than that (ε = 0.2%) between Fe23Zr6and BCC, leading to a significant change in Fe2M particles. Moreover, the morphology of Fe2M particles in solutionized-aged state is also different from that in rolled-aged state. Consequently, the yield strength (σYS = 410 MPa) of the solutionized-aged alloy is much lower than that (σYS = 560 MPa) of the rolled-aged alloy, which is ascribed to that the strengthening contribution (σor = 48 MPa) induced by short-rod particles is less than that (σor = 153 MPa) of spherical particles.