Stabilizing a three-center single-electron metal–metal bond in a fullerene cage

Trimetallic carbide clusterfullerenes (TCCFs) encapsulating a quinary M3C2 cluster represent a special family of endohedral fullerenes with an open-shell electronic configuration. Herein, a novel TCCF based on a medium-sized rare earth metal, dysprosium (Dy), is synthesized for the first time. The molecular structure of Dy3C2@Ih(7)-C80 determined by single crystal X-ray diffraction shows that the encapsulated Dy3C2 cluster adopts a bat ray configuration, in which the acetylide unit C2 is elevated above the Dy3 plane by ∼1.66 Å, while Dy–Dy distances are ∼3.4 Å. DFT computational analysis of the electronic structure reveals that the endohedral cluster has an unusual formal charge distribution of (Dy3)8+(C2)2−@C806− and features an unprecedented three-center single-electron Dy–Dy–Dy bond, which has never been reported for lanthanide compounds. Moreover, this electronic structure is different from that of the analogous Sc3C2@Ih(7)-C80 with a (Sc3)9+(C2)3−@C806− charge distribution and no metal–metal bonding

Immunogenicity of a silica nanoparticle-based SARS-CoV-2 vaccine in mice

Safe and effective vaccines have been regarded early on as critical in combating the COVID-19 pandemic. Among the deployed vaccine platforms, subunit vaccines have a particularly good safety profile but may suffer from a lower immunogenicity compared to mRNA based or viral vector vaccines. In fact, this phenomenon has also been observed for SARS-CoV-2 subunit vaccines comprising the receptor-binding domain (RBD) of the spike (S) protein. Therefore, RBD-based vaccines have to rely on additional measures to enhance the immune response. It is well accepted that displaying antigens on nanoparticles can improve the quantity and quality of vaccine-mediated both humoral and cell-mediated immune responses. Based on this, we hypothesized that SARS-CoV-2 RBD as immunogen would benefit from being presented to the immune system via silica nanoparticles (SiNP). Herein we describe the preparation, in vitro characterization, antigenicity and in vivo immunogenicity of SiNPs decorated with properly oriented RBD in mice. We found our RBD-SiNP conjugates show narrow, homogeneous particle distribution with optimal size of about 100 nm for efficient transport to and into the lymph node. The colloidal stability and binding of the antigen was stable for at least 4 months at storage- and in vivo-temperatures. The antigenicity of the RBD was maintained upon binding to the SiNP surface, and the receptor-binding motif was readily accessible due to the spatial orientation of the RBD. The particles were efficiently taken up in vitro by antigen-presenting cells. In a mouse immunization study using an mRNA vaccine and spike protein as benchmarks, we found that the SiNP formulation was able to elicit a stronger RBD-specific humoral response compared to the soluble protein. For the adjuvanted RBD-SiNP we found strong S-specific multifunctional CD4+ T cell responses, a balanced T helper response, improved auto- and heterologous virus neutralization capacity, and increased serum avidity, suggesting increased affinity maturation. In summary, our results provide further evidence for the possibility of optimizing the cellular and humoral immune response through antigen presentation on SiNP

Immunogenicity of a silica nanoparticle-based SARS-CoV-2 vaccine in mice

Safe and effective vaccines have been regarded early on as critical in combating the COVID-19 pandemic. Among the deployed vaccine platforms, subunit vaccines have a particularly good safety profile but may suffer from a lower immunogenicity compared to mRNA based or viral vector vaccines. In fact, this phenomenon has also been observed for SARS-CoV-2 subunit vaccines comprising the receptor-binding domain (RBD) of the spike (S) protein. Therefore, RBD-based vaccines have to rely on additional measures to enhance the immune response. It is well accepted that displaying antigens on nanoparticles can improve the quantity and quality of vaccine-mediated both humoral and cell-mediated immune responses. Based on this, we hypothesized that SARS-CoV-2 RBD as immunogen would benefit from being presented to the immune system via silica nanoparticles (SiNPs). Herein we describe the preparation, in vitro characterization, antigenicity and in vivo immunogenicity of SiNPs decorated with properly oriented RBD in mice. We found our RBD-SiNP conjugates show narrow, homogeneous particle distribution with optimal size of about 100 nm for efficient transport to and into the lymph node. The colloidal stability and binding of the antigen was stable for at least 4 months at storage- and in vivo-temperatures. The antigenicity of the RBD was maintained upon binding to the SiNP surface, and the receptor-binding motif was readily accessible due to the spatial orientation of the RBD. The particles were efficiently taken up in vitro by antigen-presenting cells. In a mouse immunization study using an mRNA vaccine and spike protein as benchmarks, we found that the SiNP formulation was able to elicit a stronger RBD-specific humoral response compared to the soluble protein. For the adjuvanted RBD-SiNP we found strong S-specific multifunctional CD4+ T cell responses, a balanced T helper response, improved auto- and heterologous virus neutralization capacity, and increased serum avidity, suggesting increased affinity maturation. In summary, our results provide further evidence for the possibility of optimizing the cellular and humoral immune response through antigen presentation on SiNP

Robust Nonlinear Control Scheme for Electro-Hydraulic Force Tracking Control with Time-Varying Output Constraint

This paper presents a robust nonlinear control scheme with time-varying output constraint for the electro-hydraulic force control system (EHFCS). Two typical double-rod symmetrical hydraulic cylinders are employed to simulate force environments in the EHFCS. Therefore, in order to improve the performance of the EHFCS, firstly, the model of the EHFCS is established with taking external disturbances, parameter uncertainties as well as structural vibrations into consideration. Secondly, in order to estimate external disturbances, parameter uncertainties and structural vibrations in the EHFCS and compensate them in the following robust controller design, two disturbance observers (DOs) are designed according to the nonlinear system model. Thirdly, with two estimation values from two DOs, a time-varying constraint-based robust controller (TVCRC) is presented in detail. Moreover, the stability of the proposed controller is analyzed by defining a proper Lyapunov functions. Finally, in order to validate the performance of the proposed controller, a series of simulation studies are conducted using the MATLAB/Simulink software. These simulation results give a fine proof of the efficiency of the proposed controller. What’s more, an experimental setup of the EHFCS is established to further validate the performance. Comparative experimental results show that the proposed controller exhibits better performance than the TVCRC without two DOs and a conventional proportional integral (PI) controller

Robust Nonlinear Control Scheme for Electro-Hydraulic Force Tracking Control with Time-Varying Output Constraint

This paper presents a robust nonlinear control scheme with time-varying output constraint for the electro-hydraulic force control system (EHFCS). Two typical double-rod symmetrical hydraulic cylinders are employed to simulate force environments in the EHFCS. Therefore, in order to improve the performance of the EHFCS, firstly, the model of the EHFCS is established with taking external disturbances, parameter uncertainties as well as structural vibrations into consideration. Secondly, in order to estimate external disturbances, parameter uncertainties and structural vibrations in the EHFCS and compensate them in the following robust controller design, two disturbance observers (DOs) are designed according to the nonlinear system model. Thirdly, with two estimation values from two DOs, a time-varying constraint-based robust controller (TVCRC) is presented in detail. Moreover, the stability of the proposed controller is analyzed by defining a proper Lyapunov functions. Finally, in order to validate the performance of the proposed controller, a series of simulation studies are conducted using the MATLAB/Simulink software. These simulation results give a fine proof of the efficiency of the proposed controller. What’s more, an experimental setup of the EHFCS is established to further validate the performance. Comparative experimental results show that the proposed controller exhibits better performance than the TVCRC without two DOs and a conventional proportional integral (PI) controller

Low Contrast Infrared Target Detection Method Based on Residual Thermal Backbone Network and Weighting Loss Function

Infrared (IR) target detection is an important technology in the field of remote sensing image application. The methods for IR image target detection are affected by many characteristics, such as poor texture information and low contrast. These characteristics bring great challenges to infrared target detection. To address the above problem, we propose a novel target detection method for IR images target detection in this paper. Our method is improved from two aspects: Firstly, we propose a novel residual thermal infrared network (ResTNet) as the backbone in our method, which is designed to improve the feature extraction ability for low contrast targets by Transformer structure. Secondly, we propose a contrast enhancement loss function (CTEL) that optimizes the weights about the loss value of the low contrast targets’ prediction results to improve the effect of learning low contrast targets and compensate for the gradient of the low-contrast targets in training back propagation. Experiments on FLIR-ADAS dataset and our remote sensing dataset show that our method is far superior to the state-of-the-art ones in detecting low-contrast targets of IR images. The mAP of the proposed method reaches 84% on the FLIR public dataset. This is the best precision in published papers. Compared with the baseline, the performance on low-contrast targets is improved by about 20%. In addition, the proposed method is state-of-the-art on the FLIR dataset and our dataset. The comparative experiments demonstrate that our method has strong robustness and competitiveness

Low Contrast Infrared Target Detection Method Based on Residual Thermal Backbone Network and Weighting Loss Function

Infrared (IR) target detection is an important technology in the field of remote sensing image application. The methods for IR image target detection are affected by many characteristics, such as poor texture information and low contrast. These characteristics bring great challenges to infrared target detection. To address the above problem, we propose a novel target detection method for IR images target detection in this paper. Our method is improved from two aspects: Firstly, we propose a novel residual thermal infrared network (ResTNet) as the backbone in our method, which is designed to improve the feature extraction ability for low contrast targets by Transformer structure. Secondly, we propose a contrast enhancement loss function (CTEL) that optimizes the weights about the loss value of the low contrast targets’ prediction results to improve the effect of learning low contrast targets and compensate for the gradient of the low-contrast targets in training back propagation. Experiments on FLIR-ADAS dataset and our remote sensing dataset show that our method is far superior to the state-of-the-art ones in detecting low-contrast targets of IR images. The mAP of the proposed method reaches 84% on the FLIR public dataset. This is the best precision in published papers. Compared with the baseline, the performance on low-contrast targets is improved by about 20%. In addition, the proposed method is state-of-the-art on the FLIR dataset and our dataset. The comparative experiments demonstrate that our method has strong robustness and competitiveness

Research on Adaptive Friction Compensation of Digital Hydraulic Cylinder Based on LuGre Friction Model

This paper aims to eliminate nonlinear friction from the performance of the digital hydraulic cylinder to enable it to have good adaptive ability. First, a mathematical model of a digital hydraulic cylinder based on the LuGre friction model was established, and then a dual-observer structure was designed to estimate the unobservable state variables in the friction model. The Lyapunov method is used to prove the global asymptotic stability of the closed-loop system using the adaptive friction compensation method. Finally, Simulink is used to simulate the system performance. The simulation results indicate that the addition of adaptive friction compensation control can effectively reduce system static error, suppress system limit loop oscillation, “position decapitation,” “speed dead zone,” and low-speed creep phenomena, and improve the overall performance of the digital hydraulic cylinder. The control method has practical application value for improving the performance index of the digital hydraulic cylinder

Sensitivity Analysis and Experimental Verification of Bolt Support Parameters Based on Orthogonal Experiment

This paper presents a unified supporting parameter optimization procedure for the coupled bolt-rock systems by using the orthogonal experimental methods. Convergence of surrounding rock surface and deformations in the rock are taken as the objective functions for the stability of the surrounding rock of the roadway. The key support parameters of the bolt are considered as input variables. The simulation software FLAC3D is employed to develop the mechanical model for the coupled bolt-rock system and the objective functions of the coupled system are therefore obtained in the software. Combining the variance and multivariate linear regression analysis, an approach is derived to investigate the sensitivity of the support parameters to the objective functions. The corresponding support parameters are then optimized. The 15106 working of a practical mine in Yangquan is taken as an example. According to the similar simulation theory, corresponding simulation experiments are performed. Thus, the proposed method is validated and its robust performance for optimization of supporting parameters of the bolt is also demonstrated. The method provides a theoretical basis for the determination of bolt support parameters for mining roadway in a fully mechanized mining face

Effect of Ammonium Sulfide on Sulfidization Flotation of Malachite

Recently, several studies have shown the positive effect of sulfidization flotation on malachite surfaces and its enhancing methods. Therefore, this paper was focused on the effect of ammonium sulfide and sodium sulfide on the sulfidization of malachite, respectively; this was investigated using different devices such as the micro-flotation tests, Zeta potential measurements, ToF–SIMS, XPS analysis, and FTIR. Thus, Fourier transform infrared spectroscopy results demonstrated that a new characteristic peak of Cu-S bonds was formed and adsorbed on malachite surfaces at 1694 cm−1, as confirmed by XPS analysis. Notably, malachite with ammonium sulfide ions had a significantly higher flotation recovery than malachite with an excess of sodium sulfide ions, as concerns of sulfidization types. Conclusively, all the experiments in this study confirmed that additional copper sulfide products were formed on the malachite surface, increasing the hydrophobicity of the malachite