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Dynamic models that consider multiple nonlinear factors including the two-dimensional deformation and higher-order modes are too computationally complex to be suitable for real-time control of the rotating Euler-Bernoulli beam. This article proposes a new dynamic modeling method according to the assumed mode method. The new modeling method not only has high modeling accuracy but also has a brief mathematical expression. In addition, based on the new modeling method, a neural network sliding mode control strategy using the saturation function is designed to improve the rotational accuracy of the Euler-Bernoulli beam. In the control law design, the saturation function is proposed instead of the unit step function to reduce the chattering phenomenon. Simulation and control experiments describe that the new dynamic modeling method has higher modeling accuracy than the modeling method based on the one-dimensional deformation; the proposed strategy can effectively decrease the rotation angle tracking error of the rotating Euler-Bernoulli beam and improve the control accuracy. [ABSTRACT FROM AUTHOR]

The insulated bearing may be damaged when operating under the action of current. Firstly, a novel dynamic model of insulated bearing-steel pedestal system with shaft current damage is proposed, and the model is solved based on the Runge-Kutta algorithm. Then, the model is verified by the experimental results. Based on the solution results of the dynamic model, the influence of mass and damage on the vibration signal is analyzed, the effect of damage on the stability of the insulated bearing-steel pedestal system is studied, and the influence of radial clearance on the vibration characteristics of the insulated bearing-steel pedestal system is discussed. The results indicate that, the vibration acceleration signal of the pedestal shows a positive correlation with the mass mi and the mass mo. As the length of damage increases, a few points begin to leave the quasi-periodic ring, and the quasi-periodic ring in Poincaré map gradually breaks. The coupling effect of shaft current damage and radial clearance makes the insulated bearing-steel pedestal system easier to enter an unstable motion state. [ABSTRACT FROM AUTHOR]

The shared energy storage system is recognized as a promising business model for the coordinated operation of integrated energy systems (IES) to improve the utilization of energy storage and the consumption of renewable energy. As the hydrogen energy gradually receives more attention, this paper constructs the structure of a hybrid hydrogen energy storage system shared by an IES alliance in a dynamic pricing mode. A bi-level optimization model for the shared hybrid hydrogen energy storage system (SHHESS) is proposed to optimize the capacity configuration decisions and the pricing strategy jointly. The upper level determines the capacity and dynamic price of SHHESS with maximum profits and the lower level obtains the optimal operation of the IES alliance minimizing the total operation costs. The proposed model is solved by an improved PSO-GA algorithm and CPLEX solver. Finally, numerical tests are conducted in different scenarios. The results show that the hybrid energy storage system improves the daily profits of SHHESS by 70.3% and 5.44%, and reduces the renewable energy curtailment by 80.93% and 48.92% respectively compared to the battery-only and hydrogen-only systems. Additionally, the daily operation cost of the IES alliance is 35.2% lower than the individual operation scenario. The proposed model confirms the feasibility and superiority of the hybrid hydrogen energy storage system in a sharing business mode. • Design an interactive structure of a shared hybrid hydrogen energy storage system. • Propose a bi-level planning optimization framework for shared hybrid hydrogen energy storage. • The dynamic price of energy storage sharing service is optimized. • Determine the optimal operation strategy of the integrated energy system alliance. • Propose a hybrid method combining an improved PSO-GA and CPLEX optimizer. [ABSTRACT FROM AUTHOR]

The (re)hemorrhage in patients with sporadic cerebral cavernous malformations (CCM) was the primary aim for CCM management. However, accurately identifying the potential (re)hemorrhage among sporadic CCM patients in advance remains a challenge. This study aims to develop machine learning models to detect potential (re)hemorrhage in sporadic CCM patients. This study was based on a dataset of 731 sporadic CCM patients in open data platform Dryad. Sporadic CCM patients were followed up 5 years from January 2003 to December 2018. Support vector machine (SVM), stacked generalization, and extreme gradient boosting (XGBoost) were used to construct models. The performance of models was evaluated by area under receiver operating characteristic curves (AUROC), area under the precision-recall curve (PR-AUC) and other metrics. A total of 517 patients with sporadic CCM were included (330 female [63.8%], mean [SD] age at diagnosis, 42.1 [15.5] years). 76 (re)hemorrhage (14.7%) occurred during follow-up. Among 3 machine learning models, XGBoost model yielded the highest mean (SD) AUROC (0.87 [0.06]) in cross-validation. The top 4 features of XGBoost model were ranked with SHAP (SHapley Additive exPlanations). All-Elements XGBoost model achieved an AUROCs of 0.84 and PR-AUC of 0.49 in testing set, with a sensitivity of 0.86 and a specificity of 0.76. Importantly, 4-Elements XGBoost model developed using top 4 features got a AUROCs of 0.83 and PR-AUC of 0.40, a sensitivity of 0.79, and a specificity of 0.72 in testing set. Two machine learning-based models achieved accurate performance in identifying potential (re)hemorrhages within 5 years in sporadic CCM patients. These models may provide insights for clinical decision-making. [ABSTRACT FROM AUTHOR]

The raceway damage of the bearing restricts the operation stability of the system. Therefore, in the case of damage, simulating vibration response and predicting the performance of the shaft-cylindrical roller-bearing-pedestal system have high research value. According to the structural characteristics and the force transfer relationship, a dynamic model of the shaft-cylindrical roller-bearing-pedestal system is established in this paper. Then, the vibration response of the system is simulated by Runge–Kutta algorithm and measured by experiment. Finally, the effects of load and speed, damage size, and radial clearance on the dynamic performance are investigated. The simulation and measurement results indicate that the load F and the speed N can promote the enhancement of the vibration acceleration signal. As the damage length continues to increase, the ring in the Poincaré map begins to break, and the system transits from quasi-periodic to chaotic motion. The vibration signal is more affected by the damage size than by the damage location. When the radial clearance increases from 5 × 10−6 m to 15 × 10−6 m, the PTP value increases from 23.83 m·s−2 to 61.36 m·s−2. [ABSTRACT FROM AUTHOR]

Long-term spaceflight is known to induce disruptions in circadian rhythms, which are driven by a central pacemaker located in the suprachiasmatic nucleus (SCN) of the hypothalamus, but the underlying molecular mechanisms remain unclear. Here, we developed a rat model that simulated microgravity and isolation environments through tail suspension and isolation (TSI). We found that the TSI environment imposed circadian disruptions to the core body temperature, heart rate, and locomotor-activity rhythms of rats, especially in the amplitude of these rhythms. In TSI model rats' SCNs, the core circadian gene NR1D1 showed higher protein but not mRNA levels along with decreased BMAL1 levels, which indicated that NR1D1 could be regulated through post-translational regulation. The autophagosome marker LC3 could directly bind to NR1D1 via the LC3-interacting region (LIR) motifs and induce the degradation of NR1D1 in a mitophagy-dependent manner. Defects in mitophagy led to the reversal of NR1D1 degradation, thereby suppressing the expression of BMAL1. Mitophagy deficiency and subsequent mitochondrial dysfunction were observed in the SCN of TSI models. Urolithin A (UA), a mitophagy activator, demonstrated an ability to enhance the amplitude of core body temperature, heart rate, and locomotor-activity rhythms by prompting mitophagy induction to degrade NR1D1. Cumulatively, our results demonstrate that mitophagy exerts circadian control by regulating NR1D1 degradation, revealing mitophagy as a potential target for long-term spaceflight as well as diseases with SCN circadian disruption. [ABSTRACT FROM AUTHOR]

We demonstrate enhanced acoustic sensing arising from the synergy between resonator-based acoustic sensor and deep learning. We numerically verify that both vibration amplitude and phase are enhanced and preserved at and off the resonance in our compact acoustic sensor housing three cavities. In addition, we experimentally measure the response of our sensor to single-frequency and siren signals, based on which we train convolutional neural networks (CNNs). We observe that the CNN trained by using both amplitude and phase features achieve the best accuracy on predicting the incident direction of both types of signals. This is even though the signals are broadband and affected by noise thought to be difficult for resonators. We attribute the improvement to a complementary effect between the two features enabled by the combination of resonant effect and deep learning. This observation is further supported by comparing to the CNNs trained by the features extracted from signals measured on reference sensor without resonators, whose performances fall far behind. Our results suggest the advantage of this synergetic approach to enhance the sensing performance of compact acoustic sensors on both narrow- and broad-band signals, which paves the way for the development of advanced sensing technology that has potential applications in autonomous driving systems to detect emergency vehicles. [ABSTRACT FROM AUTHOR]

AbstractThe study of dynamic performance and adaptive control of variable stiffness actuators with time-varying parameters is significant for the realization of stable and efficient human-computer interaction. In this paper, for the previously proposed variable stiffness actuator, the dynamics model of the variable stiffness actuator system is established according to the two-inertia-system theory, and the effects of time-varying parameters on the dynamic performance of the variable stiffness actuator system are analyzed. Then the adaptive control strategy of the variable stiffness actuator system with time-varying parameters is studied, and the correctness and effectiveness of the control strategy are verified experimentally. The results show that the time-varying parameters have a more obvious effect on the dynamic performance of the variable stiffness actuator system, and the difficulty in designing the system control strategy, which is caused by the complex dynamics modeling of variable stiffness actuator systems with time-varying parameters, can be effectively solved by using the proposed adaptive control strategy. Moreover, the control strategy has good stability and generalization ability. [ABSTRACT FROM AUTHOR]

A series of carbon sphere supported with adjustable alkyl length substitutes polymeric ionic liquids bearing hydroxylamino-anchored functional groups by covalent connection were fabricated from copolymerization of carbon sphere with vinyl based monomeric ionic liquids, which were constructed from 1-glycidyl-3-vinylimidazolium bromide and alkyl amines. The carbon sphere hybrid polymeric ionic liquids were characterized by FT-IR, SEM–EDS, N2 adsorption/desorption isotherm, elemental analysis, 13C MAS NMR and XPS, which were candidated as heterogeneous catalysts for CO2-epoxide cycloaddition reactions to product cyclic carbonates at mild conditions without co-catalyst and metal ion. The introduced functional groups on carbon sphere could accelerate the reaction process and yields of above 90% were obtained for various cyclic carbonates under optimized conditions. Finally, kinetic experiments were also carried out to reveal reaction mechanism and the activated energy was determined as 114.9 kJ/mol. Therefore, this study provides a new approach to fabricate multifunctional heterogeneous materials for coupling reaction of CO2 under mild conditions. [ABSTRACT FROM AUTHOR]

Due to the unique ability to mimic natural enzymes, single-atom nanoenzymes (SAE) have garnered significant attention and research in tumor therapy. However, their efficacy often faces challenges in terms of drug delivery methods, and the research regarding their applications in radiotherapy is scarce. Herein, we introduce a light-controlled SAE hydrogel platform (SH) for glutathione-depletion-mediated low-dose radiotherapy. The SH incorporates a Cu single-atom enzyme (CuSA), and upon irradiation with 1064 nm near-infrared light, the CuSA can convert light energy into heat, which in turn degrades the hydrogel, enabling the release of CuSA into tumor cells or tissues. The diffused CuSA not only can facilitate the conversion of H2O2 into hydroxyl radicals (•OH), but also can effectively depletes cellular glutathione. This leads to increased sensitivity of tumor cells to radiotherapy, resulting in enhanced cytotoxicity even at low doses. The animal study results further confirmed the good tumor-killing efficacy of this SH system. To the best of our knowledge, this stands as the pioneering report on leveraging a single-atom enzyme for GSH depletion-mediated low-dose radiotherapy. [ABSTRACT FROM AUTHOR]

Highly accurate data on urban and rural settlement (URS) are essential for urban planning and decision-making in response to climate and environmental changes. This study developed an optimal random forest classification model for URSs based on spectral–topographic–radar polarization features using Landsat 8, NASA DEM, and Sentinel-1 SAR as the remote-sensing data sources. An optimal urban and rural settlement boundary (URSB) extraction technique based on morphological and pixel-level statistical methods was established to link discontinuous URSs and improve the accuracy of URSB extraction. An optimal random forest classification model for URSs was developed, as well as a technique to optimize URSB, using the Google Earth Engine (GEE) platform. The URSB of Xining, China, in 2020 was then extracted at a spatial resolution of 30 m, achieving an overall accuracy and Kappa coefficient of 96.21% and 0.92, respectively. Compared to using a single spectral feature, these corresponding metrics improved by 16.21% and 0.35, respectively. This research also demonstrated that the newly constructed Blue Roof Index (BRI), with enhanced blue roof features, is highly indicative of URSs and that the URSB was best extracted when the window size of the structural elements was 13 × 13. These results can be used to provide technical support for obtaining highly accurate information on URSs. [ABSTRACT FROM AUTHOR]

Creating a high‐fidelity railroad station model to match the physical details of hundreds of tracks and switches is never a trivial task. The manual modeling approach often costs engineers significant efforts and constrains the generality and extensivity of many advanced methods. Taking advantage that many stations are drawn proportionally into two‐dimensional drawing exchange format (DXF) files via state‐of‐the‐art computer‐aided design (CAD) techniques, this paper proposed an efficient solution to convert DXF files into meaningful station models. The proposed solution consists of two phases (1) converting graphic basic primitives without explicit engineering interpretations into recognizable railroad symbols and (2) modeling undirected railroad station graphs with necessary configurations such as endpoints and routes. The proposed solution is developed into a graphic user interface application with minimal user interactions and subsequently tested at several real‐world passenger stations in Asia for its validity, productivity, and applicability. [ABSTRACT FROM AUTHOR]

The mission success probability (MSP) is a critical indicator for phased mission systems (PMSs). In the modern aerospace industry, redundancy techniques, including component/phase redundancy, are commonly seen to increase the MSP of the whole system. These component/phase redundancies make the reliability analysis more complex. Meanwhile, one or more components are required for normal working for different subsystems, called the K/N structure. In this article, a Markov‐process method is proposed for PMS with K/N subsystems and different redundancy strategies. Then, a universal system optimization model is proposed to optimize system structure and redundancy strategies for all subsystems at the same time. Then, an improved genetic algorithm (GA) is used to resolve the optimization problem. At last, a propulsion system is used as an engineering case, showing the proposed binary decision diagram‐based method. [ABSTRACT FROM AUTHOR]

Fused silica was polished to a high quality by a CO2 laser beam with a rapid scanning rate. The rapid scanning rate produced a line laser heat source, resulting in a "polishing line" during the polishing process. The Taguchi method was used to evaluate the comprehensive influence of polishing process parameters on the polishing qualities. Four factors, namely the length of laser reciprocating scanning (A), laser beam scanning speed (B), feed speed (C), and defocusing amount (D), were investigated in this study. The optimal process parameter combination (A1B1C1D1) was obtained. The surface roughness of fused silica was reduced from Ra = 0.157 μm to 0.005 μm. Through analysis of variance (ANOVA), it was found that laser beam scanning speed (B) had a significant influence on the polishing quality. The interaction of the two factors plays a decisive role in the determination of the best process parameters, and the influence of other multi-factor interaction can be ignored; the interaction between A × B is the largest, with a contribution of 42.69%. [ABSTRACT FROM AUTHOR]

Based on the structure of damaged bearing, a nonlinear dynamic model is proposed. The nonlinear vibration response is obtained by solving the dynamic equation of the bearing system. Firstly, the influence of radial load and rotational speed on the nonlinear vibration response of the bearing system is analyzed. Then, the different vibration characteristics of the system when the inner and outer raceways of the bearing are damaged are discussed. Finally, the influence of the degree of shaft current damage on the nonlinear characteristics of the bearing system is studied. The results indicate that the bearing system presents bifurcation, jump, and chaos with the change of radial load. With the increase of the rotational speed, the path of the bearing system from chaos to quasi-periodic changes. With the increase of the degree of shaft current damage, the system gradually transitions from a stable state to a chaotic state. [ABSTRACT FROM AUTHOR]

Flexible space structures play an invaluable role in space operation tasks as large attachments to spacecraft and artificial satellites. Due to the characteristics of flexibility and slenderness, flexible space structures will inevitably cause flexible deformation and vibrate during motion, which will affect the rotation control accuracy. To solve this problem, this paper proposes a rotation tracking control strategy based on sliding mode controller with neural network compensation. The control law is designed according to the dynamic model established by the new flexible deformation description method. Firstly, according to the new flexible deformation description method, the dynamic model of space flexible structures is established by the assumed modal method and Lagrange principle. Through a comparison of the accuracy of the dynamics model deformation, it is found that the new flexible deformation description method has high model accuracy. Based on the space flexible structures' dynamics model, the sigmoid function is proposed as the convergence law for designing the sliding mode controller. Besides, neural networks are proposed to identify and compensate for the disturbing torque caused by ignoring nonlinear factors. Finally, the effectiveness of the sliding mode controller with neural network compensation is validated by simulation and ground control experiments. [ABSTRACT FROM AUTHOR]

High dynamic range imaging (HDRI) is an essential task in remote sensing, enhancing low dynamic range (LDR) remote sensing images and benefiting downstream tasks, such as object detection and image segmentation. However, conventional frame-based HDRI methods may encounter challenges in real-world scenarios due to the limited information inherent in a single image captured by conventional cameras. In this paper, an event-based remote sensing HDR imaging framework is proposed to address this problem, denoted as ERS-HDRI, which reconstructs the remote sensing HDR image from a single-exposure LDR image and its concurrent event streams. The proposed ERS-HDRI leverages a coarse-to-fine framework, incorporating the event-based dynamic range enhancement (E-DRE) network and the gradient-enhanced HDR reconstruction (G-HDRR) network. Specifically, to efficiently achieve dynamic range fusion from different domains, the E-DRE network is designed to extract the dynamic range features from LDR frames and events and perform intra- and cross-attention operations to adaptively fuse multi-modal data. A denoise network and a dense feature fusion network are then employed for the generation of the coarse, clean HDR image. Then, the G-HDRR network, with its gradient enhancement module and multiscale fusion module, performs structure enforcement on the coarse HDR image and generates a fine informative HDR image. In addition, this work introduces a specialized hybrid imaging system and a novel, real-world event-based remote sensing HDRI dataset that contains aligned remote sensing LDR images, remote sensing HDR images, and concurrent event streams for evaluation. Comprehensive experiments have demonstrated the effectiveness of the proposed method. Specifically, it improves state-of-the-art PSNR by about 30% and the SSIM score by about 9% on the real-world dataset. [ABSTRACT FROM AUTHOR]

A manipulator that contains both flexible joints and flexible loads is called a dual-flexible manipulator, whose vibration is affected by bearing friction torque and double flexibilities. This vibration phenomenon will reduce the motion accuracy in dual-flexible manipulators. In this study, an adaptive PI control strategy using a nonlinear disturbance observer (DOB) is proposed to reduce speed fluctuations of the servo system, thereby suppressing the vibration. First, a mechanical model of the dual-flexible manipulator considering bearing frictions was established. Then, the adaptive law of the PI controller was proposed by the Lyapunov stability theorem. The optimal values of controller parameters were obtained by the adaptive law. Finally, the numerical simulation and control experiments of the dual-flexible manipulator prove that the control strategy can powerfully reduce the vibration. The results show that the nonlinear DOB can effectively identify the friction torque in the manipulator servo system and the adaptive PI control strategy can effectively reduce the tracking error by changing the controller parameters. The experimental results of the physical prototype show that the adaptive PI control strategy using a nonlinear DOB control strategy can reduce the acceleration in the vibration sensitive direction of manipulators by 41.78 % compared with the PI control strategy. Therefore, the experimental results prove the effectiveness of the proposed control strategy for reducing the vibration of dual-flexible manipulators. [ABSTRACT FROM AUTHOR]

Low‐fidelity computational models have been widely used for the computation of complex engineered systems to greatly save the computational time while sacrificing the computational precision. Model calibration can be implemented for low‐fidelity simulation models to remedy the errors of simulation results. This article proposes a modular Bayesian updating framework that considers epistemic uncertainty to achieve model calibration of low‐fidelity simulation models. The proposed framework mainly contains two steps: (1) A model calibration framework based on Bayesian theory is proposed that can simultaneously quantify the model form uncertainty, model parameter uncertainty, and the experimental measurement uncertainty, (2) the proposed method updates a low‐fidelity surrogate model via a Metropolis–Hastings (M–H) algorithm by using high‐fidelity experimental data. The proposed method greatly improves the prediction accuracy of the simulation model and enhances the computational efficiency. A mathematical example is used to testify the accuracy of the developed method, while the aerodynamics simulation of the NACA0012 airfoil is leveraged to demonstrate the engineering application. The results show that the posterior prediction mean is in better agreement with the experimental mean than the prior prediction mean, suggesting that the modular Bayesian updating method improves the prediction accuracy of low‐fidelity simulation models. [ABSTRACT FROM AUTHOR]

Bathymetry data over lake areas are not included in the current and previous NGS (National Geodetic Survey) geoid models. Lake surfaces are simply treated as land surfaces during the modeling regardless of the apparent density difference between water and rock, resulting in artificial masses that distort the model from the actual gravity field and the corresponding geoid surface. In this study, compiled high-resolution bathymetry data provided by National Centers for Environmental Information are used to identify the real volume of water bodies. Under the mass conservation principle, two strategies are deployed to properly account the water body bounded by the mean lake surface and the bathymetry indicated lake floor into the current NGS geoid modeling scheme, where the residual terrain modeling method is used to account for topographic effects. The first strategy condenses water bodies into equivalent rock masses, with the cost of changing the geometrical shape of the water body. The second one keeps the shape of the water body unchanged but replaces the water and rock densities inside each topographical column bounded by the geoid surface and the mean lake surface by an averaged density. Both strategies show up to 1-cm geoid changes when compared with the previous geoid model that does not consider bathymetric information. All three geoid models are evaluated by local GNSS/Leveling benchmarks and multi-year-multi-mission altimetry indicated mean lake surface heights. The results show that both strategies can improve the geoid model precision. And the second strategy yields more realistic results. [ABSTRACT FROM AUTHOR]

The application range of fused silica optical components can be expanded and the cost of fused silica components can be reduced by depositing the same material film on fused silica substrate. However, due to the different manufacturing process, the performance of ALD SiO2 film is lower than that of fused silica substrate, which also limits the use of this process. In this paper, ALD SiO2 film with different thicknesses were deposited, and then the structure and properties were tested. Finally, the ALD SiO2 film was treated via the annealing process. Transmission electron microscopy (TEM) showed that the ALD SiO2 film had good compactness and substrate adhesion. The Raman spectra showed that the ALD SiO2 film and substrate had the same structure, with only slight differences. The XRD pattern showed that ALD-fused silica did not crystallize before or after annealing. The infrared spectra showed that there was an obvious Si-OH defect in the ALD SiO2 film. The laser damage showed that the ALD SiO2 film had a much lower damage threshold than the fused silica substrate. The nanoindentation showed that the mechanical properties of the ALD SiO2 film were much lower than those of the fused silica substrate. After a low-temperature annealing treatment, the ALD SiO2 film Si-OH defect was reduced, the ALD SiO2 film four-member ring content was increased, the elastic modulus of the ALD SiO2 film was increased from 45.025 GPa to 68.025 GPa, the hardness was increased from 5.240 GPa to 9.528 GPa, and the ALD SiO2 film damage threshold was decreased from 5.5 J/cm2 to 1.3 J/cm2. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA), a late‐stage complication of developmental dysplasia of the hip (DDH), is a key factor leading to further degeneration of joint function. Studies have shown that Sestrin2 (SESN2) is a positive regulator in protecting articular cartilage from degradation. However, the regulatory effects of SESN2 on DDH‐OA and its upstream regulators remain obscure. Here, we first identified that the expression of SESN2 significantly decreased in the cartilage of DDH‐OA samples, with an expression trend negatively correlated with OA severity. Using RNA sequencing, we identified that the upregulation of miR‐34a‐5p may be an important factor for the decrease in SESN2 expression. Further exploring the regulation mechanism of miR‐34a‐5p/SESN2 is of great significance for understanding the mechanism of DDH occurrence and development. Mechanistically, we showed that miR‐34a‐5p could significantly inhibit the expression of SESN2, thereby promoting the activity of the mTOR signaling pathway. We also found that miR‐34a‐5p significantly inhibited SESN2‐induced autophagy, thereby suppressing the proliferation and migration of chondrocytes. We further validated that knocking down miR‐34a‐5p in vivo resulted in a significant increase in SESN2 expression and autophagy activity in DDH‐OA cartilage. Our study suggests that miR‐34a‐5p is a negative regulator of DDH‐OA, and may provide a new target for the prevention of DDH‐OA. [ABSTRACT FROM AUTHOR]

With the increase of safety requirements for human-robot interaction, variable stiffness actuators are increasingly used in joints of medical rehabilitation robots, legged mobile robots and exoskeleton-assisted robots, so the research of the variable stiffness actuator becomes more and more important. In this paper, firstly, according to the human knee joint, a low-energy nonlinear variable stiffness actuator for knee joint is proposed, it conforms to characteristics of biological joints: the actuator can be flexible when it is subjected to the small load, and the actuator can be stabilized when it is subjected to the heavy load. The realization principle of this actuator, which is combining the eccentric cam with the leaf spring, is introduced in detail, and its relatively large range of variable stiffness is accurately deduced and analyzed. Secondly, the energy cost of this actuator is reduced as much as possible by some structural designs. Finally, by experiments, the correctness and accuracy of the resistance moment and expected stiffness of the proposed nonlinear variable stiffness actuator are verified, the high bandwidth and good stability of this actuator are also verified, which meets the design principles and requirements of the actuator, and it is verified that actuator's low energy cost. [ABSTRACT FROM AUTHOR]

Flexible telescopic space manipulator (FTSM) is playing an increasingly important role in assisting astronauts to accomplish space missions. The telescopic structure leads to time-varying dynamical parameters of the FTSM, thereby reducing the tracking control accuracy. At the same time, the lightweight and large length-diameter ratios are very likely to cause the vibration phenomenon of FTSM during the motion. To solve the above problems, in the dynamics modeling, this paper uses the assumed modal method (AMM) and Lagrange principle to establish the dynamics model considering two-dimensional deformation and disturbance torque. Furthermore, the dynamics models are simplified and derived by ignoring the nonlinear terms (INTs). Besides, the influence of the simplified dynamics models on the accuracy of FTSM's deformation is analyzed by simulation. It is found that the INTs simplified dynamics model has higher modeling accuracy. Based on the INTs simplification model, the control law is designed. More importantly, the RBF neural network is used to identify and compensate for the time-varying terms and disturbance torque in the FTSM. Then the sliding mode control strategy is proposed by the hyperbolic tangent function as the approximation rate. Finally, the effectiveness of the RBF neural network compensated sliding mode control strategy is illustrated by simulation and ground control experiments of the FTSM. [ABSTRACT FROM AUTHOR]

The “non-harmonicity” problem in residual terrain modelling (RTM) is a challenging issue, causing errors exceeding 200 mGal in the RTM gravity anomaly in rugged areas. Although various methods have been proposed to address this problem, including the condensation method, regularized downward continuation methods with Taylor series expansions (TS) and spherical harmonics (SH), complete harmonic correction (HC) method, closed-form complete HC method, and Kadlec's method, their performances in gravity field determination have not been directly validated. In this study, we reviewed and evaluated these methods, especially for their performance in regional geoid determination. We found that the HC's expression for the closed-form complete method is identical to that under the unlimited Bouguer plate approximation, and Kadlec’s method is equivalent to the condensation method with the same approximation for Bouguer masses. However, the HC associated with the complete HC method shows large differences compared to other methods. This is because the upward and downward continuations in the complete HC method consider an Earth with changing total mass. To address it, we propose a new three-step approach, proved to be equivalent to the HC using the TS method. Then the performance of various HC methods is evaluated in gravity anomaly synthesis and geoid determination over a select region in Colorado, USA. The best result is achieved when using the SH method to compute RTM gravity anomalies, resulting in a geoid accuracy of ~ 1.62 cm. Involving the HC for the height anomaly in the restore procedure slightly improves the accuracy to ~ 1.56 cm. [ABSTRACT FROM AUTHOR]

A series of Al2O3 aerogel building thermal insulation materials were prepared by atmospheric pressure drying method, using propylene oxide (PO) as accelerator and adjusting the molar ratio of PO to Al. The effects of PO molar ratio on the phase structure, micro morphology, mechanical properties and thermal insulation properties of aerogel were studied. The results show that Al2 O3 aerogel is mainly composed of Boehnite at room temperature. It gradually changes from y-Al2 O3 phase to or Al2 O3 phase transition under high temperatures and the increase in PO molar ratio hinders the phase transition. Al2 O3 aerogel is formed by stacking small flake particles with a particle size of about 85160 nm. When n (PO) : n (Al)=5, the strength of aerogel skeleton is the highest, and the three-dimensional network porous structure is the most compact. With the increase of PO mow radio, the compressive strength of Al2O3 aerogel first increases and then decreases, the elastic modulus continues to increase, and the thermal first decreases and then increases. When n(PO) : n(Al) = 5, the maximum compressive strength of aerogel is 42.54 MPa, the elastic modulus is 1 454.63 MPa, and the minimum thermal conductivity is 0.0954 W/(m* K), which has excellent thermal station performance. It can be seen that the optimal molar ratio of PO is n (PO) : n (Al)=5. [ABSTRACT FROM AUTHOR]

Polyacrylamide (PAM)-glycerol (Gly)-lithium chloride (LiCl) hydrogel was prepared by salt solution immersion method, using PAM as the hydrogel matrix, Gly as the moisturizing factor and LiCl as the water absorption factor. The structure and performance of the hydrogel were characterized by scanning electron microscope, energy dispersive spectrometer, X-ray photoelectron spectrometer, Fourier infrared spectrometer, etc. Meanwhile, the effect of its application in a portable cigar moisturizing bag on the regulation of micro environment humidity was explored. The results showed that the PAM-Gly-LiCl hydrogel possessed excellent transparency and mechanical properties, with light transmittance of 90%, the maximum compression strain of 41%, compression strength of 1. 1 MPa, elongation breaking rate of 1100% and breaking strength of 0. 25 MPa. The hydrogel also displayed excellent water retention and humidity control performance. Owing to a high proportion of combined water, it could stably realize the humidity control process under different humidity environmental conditions. The humidity control range was 25%-95% of the relative humidity and kept for 500 h. The hydrogel could be applied to design as a portable cigar moisturizing bag. It could quickly sense changes in environmental humidity and make intelligent responses, stabilizing the microenvironment relative humidity inside the bag at around 65% and maintaining it for more than a week. [ABSTRACT FROM AUTHOR]

Rational design of Pt single‐atom catalysts provides a promising strategy to significantly improve the electrocatalytic activity for hydrogen evolution reaction. In this work, we presented a novel and efficient strategy for utilizing the low electron‐density region of substrate to effectively trap and confine high electron‐density metal atoms. The Pt single‐atom catalyst supported by nickel selenide with rich vacancies was prepared via a hydrothermal‐impregnation stepwise approach. Through experimental testation and DFT theoretical calculation, we confirm that Pt single atoms are well distributed at cationic vacancies of nickel selenide with loading amount of 3.2 wt. %. Moreover, the atomic Pt combined with the high electronegative Se to form Pt−Se bond as a "bridge" between single atoms and substrate for fast electron translation. This novel catalyst shows an extremely low overpotential of 45 mV at 10 mA cm−2 and an excellent stability over 120 h. Furthermore, the nickel selenide supported Pt SACs exhibits long‐term stability for practical application, which maintains a high current density of 390 mA cm−2 over 80 h with a retention of 99 %. This work points a promising direction for designing single atoms catalysts with high catalytic activity and stability for advanced green energy conversion technologies. [ABSTRACT FROM AUTHOR]

Rational design of Pt single‐atom catalysts provides a promising strategy to significantly improve the electrocatalytic activity for hydrogen evolution reaction. In this work, we presented a novel and efficient strategy for utilizing the low electron‐density region of substrate to effectively trap and confine high electron‐density metal atoms. The Pt single‐atom catalyst supported by nickel selenide with rich vacancies was prepared via a hydrothermal‐impregnation stepwise approach. Through experimental testation and DFT theoretical calculation, we confirm that Pt single atoms are well distributed at cationic vacancies of nickel selenide with loading amount of 3.2 wt. %. Moreover, the atomic Pt combined with the high electronegative Se to form Pt−Se bond as a "bridge" between single atoms and substrate for fast electron translation. This novel catalyst shows an extremely low overpotential of 45 mV at 10 mA cm−2 and an excellent stability over 120 h. Furthermore, the nickel selenide supported Pt SACs exhibits long‐term stability for practical application, which maintains a high current density of 390 mA cm−2 over 80 h with a retention of 99 %. This work points a promising direction for designing single atoms catalysts with high catalytic activity and stability for advanced green energy conversion technologies. [ABSTRACT FROM AUTHOR]

In the manipulator transmission system, there are many nonlinear inducements, such as flexibility and friction torque. It is easy to lead to fluctuations of the output rotation speed of the system, and even cause serious resonance. Therefore, PI control strategy based on fuzzy theory is proposed to solve this trouble. Firstly, the dynamic equations of the transmission system of the double flexible manipulator was established. Then, the effects of friction torque and mode order on the output characteristics of the system are analyzed. Based on the fuzzy rules, the controller parameters change constantly to reduce the oscillation of the servo system output rotation speed. Finally, numerical simulation analysis and control experiment verify the effectiveness of the control strategy described in this paper. The results are that the proposed control method can decrease the average value of the load rotation angle tracking error by 13.8 %. [ABSTRACT FROM AUTHOR]

As calcium silicate hydrate (C-S-H) is the main binding phase in concrete, understanding the doping behavior of impurity elements in it is important for optimizing the structure of cementitious materials. However, most of the current studies focus on cement clinker, and the doping mechanism of impurity elements in hydrated calcium silicate is not yet fully understood. The hydrated calcium silicate component is complex, and its structure is very similar to that of the tobermorite mineral family. In this study, the effects of three different dopants (Mg, Sr and Ba) on a representing structure of C-S-H—tobermorite—was systematically explored using densify functional theory (DFT) calculations. The calculations show that Mg doping leads to a decrease in lattice volume and causes obvious structure and coordination changes of magnesium–oxygen polyhedra. This may be the reason why high formation energy is required for the Mg-doped tobermorite. Meanwhile, doping only increases the volume of the Sr- and Ba-centered oxygen polyhedra. Specifically, the Mg-doped structure exhibits higher chemical stability and shorter interatomic bonding. In addition, although Mg doping distorts the structure, the stronger chemical bonding between Mg-O atoms also improves the compressive (~1.99% on average) and shear resistance (~2.74% on average) of tobermorillonite according to the elastic modulus and has less effect on the anisotropy of the Young's modulus. Our results suggest that Mg doping is a promising strategy for the optimized structural design of C-S-H. [ABSTRACT FROM AUTHOR]

The interline power flow controller (IPFC) presents a promising solution for managing the directional and quantitative interaction of power between different lines, facilitating a significant improvement in power system stability. Based on such a background, this paper proposes a dynamic droop control strategy to improve frequency stability through the use of IPFC equipment. To enhance the active power support ability of the IPFC, additional frequency control for the IPFC's active power control loop is designed with droop control, where each IPFC's power flow control limitations are also considered to make sure the original power of each line is controllable. Besides the addition of such basic control, the proposed droop strategy is designed in a dynamic style. The droop coefficients of each IPFC can be varied according to each line's power transmission margin, such that the power fluctuations can be shared more reasonably based on such a dynamic droop coordination strategy. The proposed methods are verified through PSCAD simulations. The results show that the dynamic droop control cannot only suppress the frequency disturbance, but also make power dispatch more efficient. [ABSTRACT FROM AUTHOR]

Early brain injury (EBI) subsequent to subarachnoid hemorrhage (SAH) is strongly associated with delayed cerebral ischemia and poor patient prognosis. Based on investigations into the molecular mechanisms underlying EBI, neurovascular dysfunction resulting from SAH can be attributed to a range of pathological processes, such as microvascular alterations in brain tissue, ionic imbalances, blood–brain barrier disruption, immune–inflammatory responses, oxidative stress, and activation of cell death pathways. Research progress presents a variety of promising therapeutic approaches for the preservation of neurological function following SAH, including calcium channel antagonists, endothelin-1 receptor blockers, antiplatelet agents, anti-inflammatory agents, and anti-oxidative stress agents. EBI can be mitigated following SAH through neuroprotective measures. To enhance our comprehension of the relevant molecular pathways involved in brain injury, including brain ischemia–hypoxic injury, neuroimmune inflammation activation, and the activation of various cell-signaling pathways, following SAH, it is essential to investigate the evolution of these multifaceted pathophysiological processes. Facilitating neural repair following a brain injury is critical for improving patient survival rates and quality of life. [ABSTRACT FROM AUTHOR]

Intracranial aneurysms (IAs) are highly prevalent in the population, and their rupture poses a significant risk of death or disability. However, the treatment of aneurysms, whether through interventional embolization or craniotomy clipping surgery, is not always safe and carries a certain proportion of morbidity and mortality. Therefore, early detection and prompt intervention of IAs with a high risk of rupture is of notable clinical significance. Moreover, accurately predicting aneurysms that are likely to remain stable can help avoid the risks and costs of over-intervention, which also has considerable social significance. Recent advances in artificial intelligence (AI) technology offer promising strategies to assist clinical trials. This review will discuss the state-of-the-art AI applications for assessing the rupture risk of IAs, with a focus on achievements, challenges, and potential opportunities. [ABSTRACT FROM AUTHOR]

• Reduce the two-dimensional automated vehicle (AV) trajectory planning to a one-dimensional speed planning problem considering conflicting moving objects (CMOs) in the environment. • Propose a parsimonious and efficient model for the AV trajectory planning problem. • Analyze the conflict areas caused by CMOs in the space-time diagram and reveal upper and lower bounds for feasible trajectories. • Propose a customized dynamic programming algorithm based on the revealed bounds to solve the investigated problem in real time. Trajectory planning for autonomous vehicles (AVs) by considering conflicting moving objects (CMOs) is a challenging problem to AV operations. This paper investigates an AV trajectory planning problem where the AV follows a given spatial path, and the trajectories of CMOs are predictable. With the spatial path fixed, the two-dimensional trajectory planning problem is reduced to a one-dimensional speed planning problem that decides the optimal speeds and accelerations of the AV along the spatial path. This paper first analyzes the conflict area caused by a single CMO in the space-time diagram, which reveals upper and lower bounds to the conflict area. Then a multi-area fusion algorithm is proposed to extend the upper and lower bound analyses to a relatively complex traffic scenario with multiple CMOs. To facilitate the computation of the investigated problem, a customized dynamic programming (DP) algorithm is developed, which employs the revealed upper and lower bounds and arriving time constraints to cut invalid trajectories at each stage. With this, the number of stages and states, as well as the computational time for solving the proposed problem, are largely reduced. A set of numerical experiments are conducted to evaluate the performance of the customized DP-based algorithm. The results show that the proposed customized DP-based algorithm can solve the investigated problem within milliseconds, which enables applications to real-time AV control. This much outperforms a state-of-the-art commercial solver, Gurobi, especially for complex traffic scenarios. We further implemented the proposed method in a real-world case study, and the results show that the trajectory generated by the proposed model has a great potential to enhance the future traffic system. [ABSTRACT FROM AUTHOR]

Expert knowledge is an important information source for reliability assessment of those systems with limited time‐to‐failure data. For a better understanding of the degradation profiles of systems, multiple experts are oftentimes invited to express their judgments and the associated uncertainties on the reliability‐related measures of the system. Evidential variables, as an alternative of uncertainty quantification, have been extensively used in expert systems to quantify the epistemic uncertainty of the elicited expertise. When eliciting the reliability‐related information by evidential variables, experts only need to express the possible ranges of reliability‐related measures and their associated probabilities. Such a type of information well caters to the experts' elicitation process. In this article, an evidential network (EN)‐based reliability assessment method is put forth by fusing multi‐source evidential information. The proposed method mainly contains three steps. In the first place, the multi‐source evidential information related to all components is elicited from experts in the form of evidential variables. Next, the evidential variable of the component reliability is assessed via a constrained optimization model by treating all pieces of multi‐source evidential information as constraints. The component reliability results are transformed into pieces of mass functions of the components' states under the theory of belief functions. The system reliability‐box and the reliability‐box over time are, therefore, calculated by the EN model by inputting all mass functions of components' states. A pipeline system and a chip cutting system are exemplified to examine the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Simple Summary: The use of computer vision technology has improved the effectiveness of individual sheep identification, but existing methods face challenges such as large parameter sizes, slow recognition speeds, and difficult deployment. To address this issue, we have made improvements and optimizations based on the Retinaface face recognition model to create a balanced speed-accuracy sheep face recognition model. The optimized model has fewer parameters, simpler computations, faster inference speeds, and higher recognition accuracy, making it well-suited for deployment on resource-constrained edge devices. This research is expected to promote the application of deep learning-based sheep face recognition methods in production. The recognition of sheep faces based on computer vision has improved the efficiency and effectiveness of individual sheep identification, providing technical support for the development of smart farming. However, current recognition models have problems such as large parameter sizes, slow recognition speed, and difficult deployment. Therefore, this paper proposes an efficient and fast basic module called Eblock and uses it to build a lightweight sheep face recognition model called SheepFaceNet, which achieves the best balance between speed and accuracy. SheepFaceNet includes two modules: SheepFaceNetDet for detection and SheepFaceNetRec for recognition. SheepFaceNetDet uses Eblock to construct the backbone network to enhance feature extraction capability and efficiency, designs a bidirectional FPN layer (BiFPN) to enhance geometric location ability, and optimizes the network structure, which affects inference speed, to achieve fast and accurate sheep face detection. SheepFaceNetRec uses Eblock to construct the feature extraction network, uses ECA channel attention to improve the effectiveness of feature extraction, and uses multi-scale feature fusion to achieve fast and accurate sheep face recognition. On our self-built sheep face dataset, SheepFaceNet recognized 387 sheep face images per second with an accuracy rate of 97.75%, achieving an advanced balance between speed and accuracy. This research is expected to further promote the application of deep-learning-based sheep face recognition methods in production. [ABSTRACT FROM AUTHOR]

Space flexible manipulator (SFM) is one of the most promising development directions of space mechanism, which is attributed to more and more spacecraft on-orbit using it to perform maintenance, capture, and assembly operations. The SFM is a complex multi-output dynamic system with nonlinear friction torque. Nonlinear friction torque makes it difficult for precise tracking control of space flexible manipulators. In this paper, nonlinear friction torque in dynamics equations of the SFM is identified by the fuzzy rules based on the universal approximation property. The nonlinear friction torque is identified to improve the preciseness of the control torque in the SFM servo system. Thus, the accuracy of the rotation angle is improved, and the tracking errors of end-effectors are reduced. Firstly, the dynamic equations of the SFM considering nonlinear friction torque are established by the Hamilton principle. Then the sliding mode control strategy is proposed to control the SFM based on adaptive fuzzy compensation. Besides, the stability of the closed-loop servo system in the SFM is proved by the Lyapunov theorem. Finally, numerical simulation analysis and ground control experiments of the SFM are carried out. The results of control experiments show that the tracking error can be reduced in this control strategy. Therefore, the control strategy can improve the control accuracy of the SFM. [ABSTRACT FROM AUTHOR]

The metal-organic frameworks-derived carbon-based electromagnetic wave (EMW) absorbing (EMWA) materials have attracted extensive attention. However, it still maintains a challenge to design the kind of materials with wide effective absorption bandwidth (EAB). Herein, a series of reduced graphene oxide (RGO) supported symmetrical lotus-like cobalt/manganese oxide/porous carbon (Co/MnO/PC/RGO) composites were synthesized by hydrothermal method and subsequent carbonization process. Impressively, the symmetrical porous structure and the special component could synergistically improve EMWA capacity. On the one hand, the symmetrical porous structure and magnetic component could optimize impedance matching, which were conducive to more EMW entering into the sample. On the other hand, the abundant heterointerfaces enhanced the interface polarization and the EMWA performance of the sample could be also regulated by the change of GO content in the mixture. When the GO content was 9 wt%, a minimum reflection loss value of −50.1 dB and the corresponding EAB value of 5.1 GHz (11.9–17.0 GHz) was achieved at a thickness of 2.0 mm. The excellent EMW performance of the sample stemmed from the increased dielectric loss and magnetic loss as well as improved impedance matching. As a consequence, this work authenticated a novel pathway to construct the carbon-based EMW absorbers with broad EAB. [Display omitted] [ABSTRACT FROM AUTHOR]

The study of position control for variable stiffness actuators is important for improving their energy efficiency and robustness. In this paper, for the previously proposed nonlinear variable stiffness actuator, firstly, a dynamic model of the variable stiffness actuator system is established based on a two-inertia-system theory. Secondly, the effects of friction and gravity factors on the dynamic performance of the system are analyzed. The results of the study show that friction and gravity have obvious effects on the dynamic characteristics of the system in the constant stiffness state, and that these effects are more complex and obvious in the variable stiffness state, which proves the reasonableness and necessity of considering friction and gravity in the dynamics modeling process. Then, in order to improve the dynamic performance of the system and make its positioning performance meet the requirements, the control strategy of the variable stiffness actuator system is studied. The results show that the sliding mode control strategy based on nonlinear disturbance observer and dynamics model is a good solution to the effect of friction and gravity on the system, and can make its position-tracking performance meet the requirements. Finally, the correctness and effectiveness of the control strategy are verified experimentally. [ABSTRACT FROM AUTHOR]

Polyanion‐type Na4Fe3(PO4)2(P2O7) (NFPP) is a promising cathode material for sodium‐ion batteries due to its low cost and high safety. Herein, a three‐dimensional (3D) holey graphene (HG) modified NFPP/C material (NFPPCHG) has been successfully prepared by a simple and scalable ball milling strategy with sodium phytate and ferrous oxalate as precursors. The introduction of HG can obviously improve the specific surface area, electronic conductivity, and ions transport performance of NFPPCHG and largely enhance its electrochemical properties. The prepared NFPPCHG delivers a high reversible capacity of 118 mAh g−1 at 0.2 C and keeps a considerable capacity of 53 mAh g−1 even at an ultrahigh rate of 100 C. NFPPCHG also shows excellent performance at 55 °C and −20 °C. Moreover, in situ distribution of relaxation time analysis further demonstrates NFPPCHG has superior electrochemical kinetics. In addition, the HC//NFPPCHG full cell displays good performance, suggesting great potential of the prepared material for practical applications. [ABSTRACT FROM AUTHOR]

Influence, as an inherently special attribute, is bound to profoundly affect a player's behavior. Meanwhile, a growing body of studies suggests that interactions among networks may be more important than isolated ones. Thus, we try our best to research whether such a setup can stimulate the sense of cooperation in spatial prisoner's dilemma games through the co-evolution of strategy imitation and interdependence networks structures. To be specific, once a player's influence exceeds the critical threshold τ , they will be permitted to build a connection with the corresponding partner on another network in a self-organized way, thus gaining additional payoff. However, a player's influence changes dynamically with the spread of strategy, resulting in time-varying connections between networks. Our results show that influence-based self-organization can facilitate cooperation, even under quite poor conditions, where cooperation cannot flourish in a single network. Furthermore, there is an optimal threshold τ to optimize the evolution of cooperation. Through microcosmic statistical analysis, we are surprised to find that the spontaneous emergence of connections between interdependence networks, especially those between cooperators, plays a key role in alleviating social dilemmas. Finally, we uncover that if the corresponding links between interdependence networks are adjusted to random ones, the evolution of cooperation will be blocked, but it is still better than relying on simple spatial reciprocity on an isolated lattice. [ABSTRACT FROM AUTHOR]

In recent years, the object‐tracking algorithm based on Siamese network has gradually become the mainstream algorithm in the field of object tracking due to its characteristics of balancing speed and accuracy. The majority of Siamese‐based trackers only use the first frame extraction template for subsequent tracking in order to prevent the introduction of noise. However, merely with a single initial template employed, it is difficult to achieve the best performance of the tracker in the face of complex tracking environments such as occlusion, motion blur, and non‐rigid deformation. Therefore, the present paper proposes a new multi‐template fusion module based on graph attention network (G‐M module), which consists of two parts: a graph‐attention‐network‐based feature‐embedding module (G module) and a multi‐template fusion module (M module). It can greatly reduce the background noise introduced by template updating while improving the tracker's ability to adapt to changes in object appearance. In addition, in order to maximize the value of G‐M module, the present paper also puts forward a two‐stage template update threshold judgment mechanism. The Pearson correlation coefficient (PCCs) is introduced and combined with APCE and the maximum response value (F‐max) to filter out reliable templates for updating. In this paper, the proposed method is applied to the SiamFC and SiamFC++ trackers. Extensive experiments on mainstream data sets, such as OTB2015, VOT2016, and GOT‐10 k, show that the proposed method can effectively update the tracking template and improve the tracker performance. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

It is vitally important to develop highly active, robust and low‐cost transition metal‐based electrocatalysts for overall water splitting in neutral solution especially at large current density. In this work, amorphous Mo‐doped NiS0.5Se0.5 nanosheets@crystalline NiS0.5Se0.5 nanorods (Am−Mo−NiS0.5Se0.5) was synthesized using a facil one‐step strategy. In phosphate buffer saline solution, the Am−Mo−NiS0.5Se0.5 shows tiny overpotentials of 48 and 209 mV for hydrogen evolution reaction (HER), 238 and 514 mV for oxygen evolution reaction (OER) at 10 and 1000 mA cm−2, respectively. Moreover, Am−Mo−NiS0.5Se0.5 delivers excellent stability for at least 300 h without obvious degradation. Theoretical calculations revealed that the Ni sites in the defect‐rich amorphous structure of Am−Mo−NiS0.5Se0.5 owns higher electron state density and strengthened the binding energy of H2O, which will optimize H adsorption/desorption energy barriers and reduce the adsorption energy of OER determining step. [ABSTRACT FROM AUTHOR]

It is vitally important to develop highly active, robust and low‐cost transition metal‐based electrocatalysts for overall water splitting in neutral solution especially at large current density. In this work, amorphous Mo‐doped NiS0.5Se0.5 nanosheets@crystalline NiS0.5Se0.5 nanorods (Am−Mo−NiS0.5Se0.5) was synthesized using a facil one‐step strategy. In phosphate buffer saline solution, the Am−Mo−NiS0.5Se0.5 shows tiny overpotentials of 48 and 209 mV for hydrogen evolution reaction (HER), 238 and 514 mV for oxygen evolution reaction (OER) at 10 and 1000 mA cm−2, respectively. Moreover, Am−Mo−NiS0.5Se0.5 delivers excellent stability for at least 300 h without obvious degradation. Theoretical calculations revealed that the Ni sites in the defect‐rich amorphous structure of Am−Mo−NiS0.5Se0.5 owns higher electron state density and strengthened the binding energy of H2O, which will optimize H adsorption/desorption energy barriers and reduce the adsorption energy of OER determining step. [ABSTRACT FROM AUTHOR]

Organic amendments are a proven method of reducing soil erosion. However, the effect of organic additives on the pore properties of soils waterlogged by extreme rainfall has been minimally investigated. In this study, we collected rainfall data, established a field experiment consisting of randomized groups, and imaged the pore structure of waterlogged soil treated with different organic amendments (9 t ha−1 of maize straw [MS], 2.37 t ha−1 of cattle manure [OF], a mixture of 9 t ha−1 of MS and 1.89 t ha−1 of cattle manure [SOF], 7.4 t ha−1 of biochar [BC], 8.1 t ha−1 of woody peat [WP], and 3 L ha−1 of polyacrylamide [PAM]) in three-dimensions by X-ray microtomography and digital image analysis, which further quantified the effects. The results showed that, compared with the control, BC increased the total porosity by 54.28% and the connected porosity by 119.75%, but did not affect the pore shape and size distribution. BC and SOF improved the soil connectivity indexes; e.g., their C/I ratios increased by 177.44% and 149.62%, and the coordination numbers increased by 6.75% and 15.76%, respectively. MS had fewer, but longer and larger, channels and throats. Extreme precipitation events were significantly negatively correlated with all connectivity indicators. This study shows that organic materials can optimize the pore structure of waterlogged soil, with BC being the most resistant to erosion. However, extreme precipitation events can counteract the benefits organic additives have on soil pore structure. [ABSTRACT FROM AUTHOR]

Cysteinyl aspartate specific proteinase-3 (Caspase-3) is an important protein involved in the apoptosis and gasdermin E (GSDME)-mediated cell pyroptosis pathways in vertebrates. A Caspase-3 homologue (designated as Cg Caspase-3) was previously identified as an immune receptor specific for lipopolysaccharide (LPS) to regulate apoptosis in the Pacific oyster Crassostrea gigas. In the present study, the binding activity of Cg Caspase-3 to different pathogen associated molecular patterns (PAMPs) and its effects on Cg GSDME translocation in haemocytes were further investigated in C. gigas. The mRNA expression of Cg Caspase-3 could be detected in all the tested tissues, including hepatopancreas, labial palp, adductor muscle, gonad, gill, mantle and haemocytes, and it was highly expressed in labial palp, gonad, haemocytes, and adductor muscle. The mRNA expression of Cg Caspase-3 in haemocytes increased significantly at 3, 24, 48 and 72 h after LPS stimulation, and it increased significantly at 6, 12, 24 and 48 h after Vibrio splendidus stimulation. The recombinant Cg Caspase-3 displayed binding activity towards LPS, mannose (MAN), peptidoglycan (PGN), and polyinosinic-polycytidylic acid potassium salt (Poly (I:C)). The positive signals of Cg GSDME on haemocyte membrane became stronger at 3 h after V. splendidus stimulation, compared with that of Seawater group, and the co-localization of Cg Caspase-3 and Cg GSDME was observed in the haemocyte membrane. After the injection of ds Cg Caspase-3, the positive signals of Cg GSDME on haemocyte membrane became weaker compared with that of EGFP-RNAi group at 24 h after V. splendidus stimulation. The results suggested that Cg Caspase-3 was able to bind diverse PAMPs and activate the translocation of Cg GSDME in haemocytes of oyster response against pathogen invasion. • The mRNA expression of Cg Caspase-3 was detected in all tested tissues and it was induced by immune stimulation. • Cg Caspase-3 displayed the binding activity to different PAMPs. • Cg Caspase-3 was able to activate translocation of Cg GSDME in haemocytes to response against pathogen invasion. [ABSTRACT FROM AUTHOR]

Space flexible robotic arms can be installed on space stations or spacecraft to perform on-orbit tasks such as capturing artificial satellites, removing space debris, and assisting astronauts in overhauling. The space flexible robotic arm is a nonlinear complex dynamic system with disturbance torque and nonlinear factors coupled with joint and load flexibility. Many nonlinear terms and disturbance torque in the dynamic equations constitute the uncertain part of the space flexible robotic arm. The space flexible robotic arm is affected by the uncertain part, which will cause trajectory tracking errors. In this paper, the improved sliding mode control strategy based on fuzzy compensation is proposed to compensate for the uncertain part to enhance the trajectory tracking accuracy. Firstly, the dynamics model of the space flexible robotic arm considering joint flexibility is established. Next, the control law of the control strategy is designed by the tanh function. Then, the adaptive law of fuzzy systems is designed by the Lyapunov stability theorem. Finally, numerical simulation analysis and prototype control experiments show that the control strategy can effectively reduce the speed fluctuation of the space flexible robotic arm. Compared with the classical sliding mode control strategy, the control strategy decreased the means of absolute error by 9.1425%, which reveals that the strategy can enhance the trajectory tracking accuracy of the space flexible robotic arm. [ABSTRACT FROM AUTHOR]