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Abstract There is not only thrust but also normal force between the primary and secondary components for the single‐side flat plate permanent magnet linear synchronous motor (PMLSM). The normal force will fluctuate periodically, which will cause friction perturbation and finally affect the positioning accuracy of linear feed system. For the single‐side flat plate PMLSM, the variation law of normal force ripple under the coupling effect of multiple effects is studied, and the method of primary component segmental design to suppress it is proposed. Firstly, the influence of the cogging effect, the end effect and the armature reaction on the normal force ripple is analysed. Meanwhile the mathematical model of normal force ripple is established. Secondly, the PMLSM with segmental primary component is introduced and its suppression mechanism to the normal force ripple is expounded. On this basis, a scheme combining the non‐integer pole slot matching with the primary component segmental design is proposed to further suppress the normal force ripple. Finally, an 18‐slot 96/5‐pole prototype is taken as an example to carry out the finite element simulation and experimental test, of which the results verify the research theory in this paper.

Abstract Background Microsatellite instability-high (MSI-H) has emerged as a significant biological characteristic of colorectal cancer (CRC). Studies reported that MSI-H CRC generally had a better prognosis than microsatellite stable (MSS)/microsatellite instability-low (MSI-L) CRC, but some MSI-H CRC patients exhibited distinctive molecular characteristics and experienced a less favorable prognosis. In this study, our objective was to explore the metabolic transcript-related subtypes of MSI-H CRC and identify a biomarker for predicting survival outcomes. Methods Single-cell RNA sequencing (scRNA-seq) data of MSI-H CRC patients were obtained from the Gene Expression Omnibus (GEO) database. By utilizing the copy number variation (CNV) score, a malignant cell subpopulation was identified at the single-cell level. The metabolic landscape of various cell types was examined using metabolic pathway gene sets. Subsequently, functional experiments were conducted to investigate the biological significance of the hub gene in MSI-H CRC. Finally, the predictive potential of the hub gene was assessed using a nomogram. Results This study revealed a malignant tumor cell subpopulation from the single-cell RNA sequencing (scRNA-seq) data. MSI-H CRC was clustered into two subtypes based on the expression profiles of metabolism-related genes, and ENO2 was identified as a hub gene. Functional experiments with ENO2 knockdown and overexpression demonstrated its role in promoting CRC cell migration, invasion, glycolysis, and epithelial-mesenchymal transition (EMT) in vitro. High expression of ENO2 in MSI-H CRC patients was associated with worse clinical outcomes, including increased tumor invasion depth (p = 0.007) and greater likelihood of perineural invasion (p = 0.015). Furthermore, the nomogram and calibration curves based on ENO2 showed potential prognosis predictive performance. Conclusion Our findings suggest that ENO2 serves as a novel prognostic biomarker and is associated with the progression of MSI-H CRC.

Abstract The induction of cuproptosis, a recently identified form of copper‐dependent immunogenic cell death, is a promising approach for antitumor therapy. However, sufficient accumulation of intracellular copper ions (Cu2+) in tumor cells is essential for inducing cuproptosis. Herein, an intelligent cuproptosis‐inducing nanosystem is constructed by encapsulating copper oxide (CuO) nanoparticles with the copper ionophore elesclomol (ES). After uptake by tumor cells, ES@CuO is degraded to release Cu2+ and ES to synergistically trigger cuproptosis, thereby significantly inhibiting the tumor growth of murine B16 melanoma cells. Moreover, ES@CuO further promoted cuproptosis‐mediated immune responses and reprogrammed the immunosuppressive tumor microenvironment by increasing the number of tumor‐infiltrating lymphocytes and secreted inflammatory cytokines. Additionally, combining ES@CuO with programmed cell death‐1 (PD‐1) immunotherapy substantially increased the antitumor efficacy in murine melanoma. Overall, the findings of this study can lead to the use of a novel strategy for cuproptosis‐mediated antitumor therapy, which may enhance the efficacy of immune checkpoint inhibitor therapy.

In this paper, the Tesla meter and magnetic force microscope were used to study the open-circuit remanence and magnetic domain structure of Nd-Fe-B permanent magnets (PMs) in high-power density permanent magnet synchronous motors (PMSMs). An experimental platform was built to simulate the internal demagnetization environment of PMSM. Nd-Fe-B PMs were subjected to high temperature, DC demagnetizing field and alternating demagnetizing field. The results show that even when the working point of Nd-Fe-B PM is higher than the knee point, demagnetization still occurs in the simulated motor environment. The relationship between macroscopic magnetic properties and magnetic domain structure is investigated. With the decrease of open-circuit remanence, the average width and the magnetization of the magnetic domain in the magnetization direction decrease. Due to the width of the magnetic domain decreasing, the number of magnetic domains increases, and the area of the domain wall increases. As a transition region with weak magnetism, the increase of the domain wall area will lead to a decrease in magnetic properties. This work is helpful to understand the demagnetization mechanism of Nd-Fe-B magnets in the PMSMs.

Due to the characteristics of high-altitude solar airplanes, the permanent magnet synchronous motors (PMSMs) require not only high torque density, but also high reliability. The balance of quality, reliability, and performance in a design proposal is particularly important. In this paper, a robust mechanical–electrical integrated optimization method for PMSMs based on 6σ theory is proposed. According to the fatigue characteristics of materials under the propeller working conditions and the uncertainty factors caused by the actual machining dimension tolerance, the electromagnetic dimension, mechanical dimension and reliability of the PMSM are connected. And a robust optimization model for the reliability and performance of the PMSMs is established. The Monte Carlo method and finite element simulation method are used to verify the correctness of the established optimization model. According to the comparison between the deterministic optimization method and the proposed optimization model, this method can significantly improve the output performance and reliability of the PMSMs.

To ensure precise positioning of the macro–micro platform with a symmetrical structure, it is crucial to mitigate the impact of various perturbations, including disturbances, as well as complex factors such as external loads, electrical noise, and model parameter variations. This paper proposes a novel macro–micro master–slave control structure that incorporates adaptive fuzzy linear active disturbance rejection control (AFLADRC). The Kp and Kd parameters of the linear state error feedback (LSEF) are dynamically tuned and adjusted using fuzzy reasoning. This approach enhances the robustness of the system and simplifies the tuning process. In addition, this paper also analyzes the symmetry of the coupling effect between macro and micro, as the coupling will affect the motor force and the reaction potential of the motor. The macro–micro platform adopts a symmetric design; the macro stage is driven by a permanent magnet synchronous linear motor (PMLSM), and the micro stage is driven by a voice coil motor. Finally, we built the macro–micro linear motion experimental platform to verify the control effect of the proposed method by conducting trajectory tracking experiments and comparison experiments.

Accurately calculating the magnetic acceleration noise is essential to designing the space inertial sensor and constructing its evaluation system. In view of the shortcomings of the magnetic acceleration noise calculation model, which considers the test mass (TM) as an ideal magnetic dipole rather than an entity, the Maxwell stress tensor method (MSTM) and virtual work principle method (VWPM), which consider the influence of the shape and size of the TM into account are adopted in this study. Through comparison, it is concluded that the non-uniformities of the internal magnetic field and magnetization intensity of the TM are the reasons for the calculation error of the model, and when the magnetic susceptibility is

Abstract The rotor of a magnetic suspension centrifugal compressor is supported by magnetic bearing, and a power failure will cause the high‐speed rotor to fall directly onto the protective bearings, affecting the reliability of the compressor. To solve this problem, this paper proposes an abnormal power failure shutdown control method with semi‐switching modulation of the inverter. Firstly, the overall scheme of abnormal power failure shutdown control is designed, and its feasibility is analysed in detail through mathematical modelling. Secondly, aiming at the non‐linear, time‐varying and gain uncertainty characteristics of the control system, a voltage control strategy based on parametric self‐regulating sliding‐mode variable structure is proposed, and the stability is analysed. Finally, the method proposed in this paper is experimentally verified, the results show that this method does not depend on the electric angle of the motor compared to existing methods, and the rotor can achieve a zero‐drop speed shutdown, which greatly improves the reliability of the magnetic suspension centrifugal compressor.

BackgroundMetabolic syndrome (MetS) is associated with poor prognosis in many cancers. However, the relationship between metabolic syndrome and overall survival (OS) in patients with colorectal cancer (CRC) remains unclear. We aimed to comprehensively analyze whether MetS could affect postoperative complications and long-term survival in patients with CRC.MethodsWe included patients who underwent CRC resection at our center between January 2016 and December 2018. Bias was reduced through propensity score matching analysis. Patients with CRC were divided into the MetS and non-MetS groups based on whether they had MetS. Univariate and multivariate analyses were used to identify risk factors affecting OS.ResultsWe included 268 patients; among them, 120 were included for further analysis after propensity score matching. There were no significant between-group differences in the clinicopathological features after matching. Compared with the non-MetS group, the MetS group had a shorter OS (P = 0.027); however, there was no significant between-group difference in postoperative complications. Multivariate analysis revealed that MetS (hazard ratio [HR] = 1.997, P = 0.042), tumor-node-metastasis stage (HR = 2.422, P = 0.003), and intestinal obstruction (HR = 2.761, P = 0.010) were independent risk factors for OS.ConclusionsMetS affects the long-term survival of patients with CRC without affecting postoperative complications.

Heel ulcer is one of the severe complications of patients with diabetes mellitus, which poses a high risk for foot infection and amputation, especially in patients with peripheral arterial disease and neuropathy. Researchers have searched for new treatments for treating diabetic foot ulcers in recent years. In this case report, we demonstrated the treatment of large ischemic ulcers for the first time in a diabetic patient. The overall treatment goal of this patient was designed to improve blood supply to her diseased lower extremities and close the ulcer. This two-stage reconstruction approach resulted in an ulcer-free, stable, plantigrade foot at postoperative follow-up.

As the electrification process of aircrafts continues to advance, the propulsion motor system, as its core component, has received more attention and research. This paper summarizes and analyzes the development status, research focus and typical cases in this field in recent years. Firstly, it analyzes the basic structure and principle of five common motors, summarizes the current status of their respective applications in electric aircrafts, and compares them to determine the most suitable type of motor for use as a propulsion motor, focusing on various performance indexes. Then, the optimized design of propulsion motors is generally divided into two categories, namely high power density and fault tolerance. Starting from the basic relationship equation of motor design, the basic method to improve the power density of motors is pointed out; at the same time, according to the basic principles and objectives of the fault tolerance of motors, the fault tolerance design is divided into two aspects, namely the redundant design and the design to improve the fault tolerance capability. Finally, this paper summarizes the current development status of the propulsion motor system and the existing problems and points out the main development direction of this field in the future, so as to provide reference for the further development of the electric propulsion system of aircraft.

Abstract This study presents an improved sub‐domain analytical model for the characteristic evaluation of the flux reversal permanent magnet machine with Halbach array magnets (FRPMM‐HAM) in rotor slot. The influence of iron saturation is considered by equating iron reluctances into airgap. Based on the different material magnetic permeabilities, the FRPMM‐HAM is divided into several regions, including slots, permanent magnets (PMs), airgap and so on. By solving the Maxwell equations in polar coordinate for each region according to the boundary conditions, the vector magnetic potential can be derived. According to the vector magnetic potential, the airgap flux density distributions are predicted and the electromagnetic characteristics are calculated. The average magnetic density of the tooth and yoke is combined with the Bertotti model to calculate the iron loss. Besides, the eddy current loss of PMs is also calculated. The accuracy of analytical results is validated via the finite element method (FEM).

A Maxwell coil is a gradient magnetic field source with high uniformity, and it is widely used in the experiment of magnetic effect in space gravitational wave detection, magnetic resonance molecular imaging, and other precision magnetic measurement experiments. In this paper, taking the square Maxwell coil as a research object, the influences of four kinds of assembly errors on the uniformity of magnetic field gradient (UOMFG) are systematically analyzed and the results are verified by simulation using the finite element method. We obtained variation rules of UOMFG changing with the four assembly errors and summarized three useful conclusions. These rules and conclusions are instructive in the design, processing, and assembly of the square Maxwell coil and are beneficial for the optimal utilization of the working area in the precision magnetic measurement experiments.

In-depth understanding of the layer-by-layer process is critical for the quality control of additive manufactured (AM) components. Besides the development of experimental techniques, computational modelling is another important way to study the AM mechanisms in detail. However, currently there is still lack of a modelling platform that integrates all the necessary physics involved in the AM process. In the present study, we develop a modelling framework that integrates a phase field method for microstructure evolution, a lattice Boltzmann method for melt pool dynamics, a modified ray-tracing method for laser-material interaction, and a minimum gravity energy algorithm for powder bed generation to simulate the single-track, powder bed fusion (PBF) process of NiTi shape memory alloy. Our simulation shows that different from keyhole depth, melt pool size does not obey the scaling law with line energy density, the keyhole depth and the overlapping ratio of laser spot vs. keyhole opening together determine the laser absorptivity. Based on the simulation finding, we also develop a self-consistent analytical model to predict the keyhole depth and the absorptivity for given scanning parameters. The present work lays a solid foundation towards quantitative understanding of multi-layer AM process.

Pancreatic cancer (PC) is one of the most fatal malignant tumors, and is commonly diagnosed at an advanced stage with no effective therapy. Metabolism-related genes (MRGs) and immune-related genes (IRGs) play considerable roles in the tumor microenvironment. Therefore, an effective prediction model based on MRGs and IRGs could aid in the prognosis of PC. In this study, differential expression analysis was performed to gain 25 intersectional genes from 857 differentially expressed MRGs (DEMRGs), and 1353 differentially expressed IRGs, from The Cancer Genome Atlas database of PC. Cox and Lasso regression were applied and a five-DEMRGs prognostic model constructed. Survival analysis, ROC values, risk curve and validation analysis showed that the model could independently predict PC prognosis. In addition, the correlation analysis suggested that the five-DEMRGs prognostic model could reflect the status of the immune microenvironment, including Tregs, M1 macrophages and Mast cell resting. Therefore, our study provides new underlying predictive biomarkers and associated immunotherapy targets.

The current morphing technologies are mostly regarded as auxiliary tools, providing additional control torques to enhance the flight maneuverability of unmanned aerial vehicles (UAVs), and they cannot exist independently of the traditional control surfaces. In this paper, we propose a tandem-wing micro aerial vehicle (MAV) with multiple variable-sweep wings, which can reduce the additional inertia forces and moments and weaken the dynamic coupling between longitudinal and lateral motion while the MAV morphs symmetrically for pitch control or asymmetrically for roll control, thereby flying without the traditional aileron and elevator. First, load experiments were conducted on the MAV to verify the structural strength of the multiple variable sweep wings, and the control moments caused by the morphing of the MAV were presented through numerical simulations. Then, the effects caused by symmetric and asymmetric morphing were investigated via dynamic response simulations based on the Kane dynamic model of the MAV, and the generated additional inertia forces and moments were also analyzed during morphing. Finally, dynamic response experiments and open-loop flight experiments were conducted. The experimental results demonstrated that the morphing mode in this study could weaken the coupling between the longitudinal and lateral dynamics and that it was feasible for attitude control without the traditional aileron and elevator while flying.

This paper is concerned with the problem of state estimation for nonlinear multi-sensor systems with cross-correlated noise and packet loss compensation. In this case, the cross-correlated noise is modeled by the synchronous correlation of the observation noise of each sensor, and the observation noise of each sensor is correlated with the process noise at the previous moment. Meanwhile, in the process of state estimation, since the measurement data may be transmitted in an unreliable network, data packet dropout will inevitably occur, leading to a reduction in estimation accuracy. To address this undesirable situation, this paper proposes a state estimation method for nonlinear multi-sensor systems with cross-correlated noise and packet dropout compensation based on a sequential fusion framework. Firstly, a prediction compensation mechanism and a strategy based on observation noise estimation are used to update the measurement data while avoiding the noise decorrelation step. Secondly, a design step for a sequential fusion state estimation filter is derived based on an innovation analysis method. Then, a numerical implementation of the sequential fusion state estimator is given based on the third-degree spherical-radial cubature rule. Finally, the univariate nonstationary growth model (UNGM) is combined with simulation to verify the effectiveness and feasibility of the proposed algorithm.

This paper presents a study on controlling the out-of-water motion of amphibious multi-rotor UAVs using a cascade control method based on the Active Disturbance Rejection Control (ADRC) algorithm. The aim is to overcome the challenges of time-varying model parameters and complex external disturbances. The research involves developing an underwater dynamic model and analyzing hydrodynamic forces to calculate theoretical inertial hydrodynamic forces and simulate viscous hydrodynamic forces. This establishes the relationship between viscous hydrodynamic forces and exit velocity. A complete air dynamic model is then established, selecting model parameters based on the center of mass position of the amphibious vehicle to enable switching from water to air. To address control algorithm instability caused by changes in model parameters, position and attitude controllers are built using the ADRC algorithm. The control effects are compared with traditional PID and sliding mode controllers (SMC) to verify the effectiveness and superiority of the proposed cascade ADRC control strategy. Experimental results show that our controller has stronger anti-interference than traditional PID and SMC controllers and can overcome control instability caused by changes in model parameters. Our research highlights the importance of using ADRC-based controllers for amphibious multi-rotor UAVs to achieve robust and stable control.

This paper presents a novel means of sensorless drive of the winding segmented permanent magnet linear motor (WS-PMLM). In order to solve the problem of the deviation of the position and speed estimation of the mover caused by the sharp changes of the inductance, flux linkage, and back electromotive force (EMF) between the segments of the WS-PMLM, a method for position estimation by the compound back-EMF is proposed to eliminate the blind spot of intersegment position estimation. In terms of speed estimation, a full-order speed observer method based on the dynamics equation is proposed, the configuration of the feedback gain of the observer is analyzed, and a simulation is used to verify that the full-order state observer (FSO) method can effectively reduce the estimated speed fluctuation in the intersegment region and that the speed estimation accuracy is ultimately improved.