Understanding the spectrum of non-motor symptoms in multiple sclerosis:insights from animal models

Multiple sclerosis is a chronic autoimmune disease of the central nervous system and is generally considered to be a non-traumatic,physically debilitating neurological disorder.In addition to experiencing motor disability,patients with multiple sclerosis also experience a variety of nonmotor symptoms,including cognitive deficits,anxiety,depression,sensory impairments,and pain.However,the pathogenesis and treatment of such non-motor symptoms in multiple scle rosis are still under research.Preclinical studies for multiple sclerosis benefit from the use of disease-appropriate animal models,including experimental autoimmune encephalomyelitis.Prior to understanding the pathophysiology and developing treatments for non-motor symptoms,it is critical to chara cterize the animal model in terms of its ability to replicate certain non-motor features of multiple sclerosis.As such,no single animal model can mimic the entire spectrum of symptoms.This review focuses on the non-motor symptoms that have been investigated in animal models of multiple sclerosis as well as possible underlying mechanisms.Further,we highlighted gaps in the literature to explain the nonmotor aspects of multiple sclerosis in expe rimental animal models,which will serve as the basis for future studies.

Correlation study between the changes of motor evoked potential and the improvement of spinal canal volume in minimally invasive transforaminal lumbar interbody fusion

Objective:To analyze the correlation between the amplitude changes of motor evoked potential(MEP),the 3D volume changes of spinal canal measuring by postoperative CT and the improvement rate of clinical symptoms after the spinal canal decompression in minimally invasive transforaminal lumbar interbody fusion(MIS-TLIF),and to explore the predictive value of the changes of both MEP amplitude and spinal canal volume in the assessment of long-term clinical prognosis in MIS-TLIF.Methods:A retrospective study of 68 patients with L4/5 spinal stenosis treated with MIS-TLIF was performed.The changes of both intraoperative MEP amplitude and 3D spinal canal volume during the spinal canal decompression,as well as the visual analogue scale(VAS)and Oswestry dysfunction index(ODI)scores in the long-term follow-up were all recorded.Results:The values of intraoperative MEP amplitude was 159.04%higher in 68 patients with MIS-TLIF after spinal canal decompression(P<0.01).The 3 postoperative 3D spinal canal volume(4.89±1.27)cm increased by 31.22%in comparison 3 with preoperative date(3.78±1.08)cm(P<0.01).The VAS and ODI scores were improved to 78.55%and 80.60%,respectively at the last follow-up(P<0.01).The improvement rate of MEP amplitude on the decompression side was positively correlated with the improvement rate of postoperative spinal canal volume(r=0.272,P=0.025).The improvement rate of postoperative spinal canal volume was positively correlated with the improvement rate of VAS and ODI at the last follow-up(r=0.656,r=0.490,P<0.01).Moreover,the improvement rate of MEP amplitude on the decompression side was also positively correlated with the improvement rate of VAS and ODI at the last follow-up(r=0.322 and 0.235,respectively,P<0.05).Conclusion:The increase of MEP amplitude after spinal canal decompression in patients with lumbar spinal stenosis treated by MIS-TLIF was closely correlated with both of the increase of spinal canal volume and the improvement of clinical symptoms.Therefore,MEP amplitude monitoring was not only the one of the important monitoring methods for predicting the prognosis of MIS-TLIF but also the reliably predictive value in the long-term clinical prognosis in MIS-TLIF.

Design of Rotor Magnetic Barrier Structure of Built-in Permanent Magnet Motor Based on Taguchi Method

In this paper,a 20kW vehicle built-in permanent magnet synchronous motor is taken as an example,and a magnetic barrier structure is added to the rotor of the motor to solve the uneven saturation problem of the rotor side magnetic bridge.This structure improves the air-gap flux density waveform of the motor by influencing the internal magnetic flux path of the motor rotor,thus improving the sine of the no-load back EMF waveform of the motor and reducing the torque ripple of the motor.At the same time,Taguchi method is used to optimize the structural parameters of the added magnetic barrier.In order to facilitate the analysis of its uneven saturation phenomenon and improve the optimization effect,a simple equivalent magnetic network(EMN)model considering the uneven saturation of rotor magnetic bridge is established in this paper,and the initial values of optimization factors are selected based on this model.Finally,the no-load back EMF waveform distortion rate,torque ripple and output torque of the optimized motor are compared and analyzed,and the influence of magnetic barrier structure parameters on the electromagnetic performance of the motor is also analyzed.The results show that the optimized motor can not change the output torque of the motor as much as possible on the basis of reducing the waveform distortion rate of no-load back EMF and torque ripple.

Elevated brain temperature under severe heat exposure impairs cortical motor activity and executive function

Background:Excessive heat exposure can lead to hyperthermia in humans,which impairs physical performance and disrupts cognitive function.While heat is a known physiological stressor,it is unclear how severe heat stress affects brain physiology and function.Methods:Eleven healthy participants were subjected to heat stress from prolonged exercise or warm water immersion until their rectal temperatures(T_(re))attained 39.5℃,inducing exertional or passive hyperthermia,respectively.In a separate trial,blended ice was ingested before and during exercise as a cooling strategy.Data were compared to a control condition with seated rest(normothermic).Brain temperature(T_(br)),cerebral perfusion,and task-based brain activity were assessed using magnetic resonance imaging techniques.Results:T_(br)in motor cortex was found to be tightly regulated at rest(37.3℃±0.4℃(mean±SD))despite fluctuations in T_(re).With the development of hyperthermia,T_(br)increases and dovetails with the rising T_(re).Bilateral motor cortical activity was suppressed during high-intensity plantarflexion tasks,implying a reduced central motor drive in hyperthermic participants(T_(re)=38.5℃±0.1℃).Global gray matter perfusion and regional perfusion in sensorimotor cortex were reduced with passive hyperthermia.Executive function was poorer under a passive hyperthermic state,and this could relate to compromised visual processing as indicated by the reduced activation of left lateral-occipital cortex.Conversely,ingestion of blended ice before and during exercise alleviated the rise in both T_(re)and T_(bc)and mitigated heat-related neural perturbations.Conclusion:Severe heat exposure elevates T_(br),disrupts motor cortical activity and executive function,and this can lead to impairment of physical and cognitive performance.

Origin of tradeoff between movement velocity and attachment duration of kinesin motor on a microtubule

Kinesin-1 motor protein is a homodimer containing two identical motor domains connected by a common long coiledcoil stalk via two flexible neck linkers. The motor can step on a microtubule with a velocity of about 1 μm·s-1and an attachment duration of about 1 s under physiological conditions. The available experimental data indicate a tradeoff between velocity and attachment duration under various experimental conditions, such as variation of the solution temperature,variation of the strain between the two motor domains, and so on. However, the underlying mechanism of the tradeoff is unknown. Here, the mechanism is explained by a theoretical study of the dynamics of the motor under various experimental conditions, reproducing quantitatively the available experimental data and providing additional predictions. How the various experimental conditions lead to different decreasing rates of attachment duration versus velocity is also explained.

Symmetric Brownian motor subjected to Lévy noise

In the past few years,attention has mainly been focused on the symmetric Brownian motor(BM)with Gaussian noises,whose current and energy conversion efficiency are very low.Here,we investigate the operating performance of the symmetric BM subjected to Lévy noise.Through numerical simulations,it is found that the operating performance of the motor can be greatly improved in asymmetric Lévy noise.Without any load,the Lévy noises with smaller stable indexes can let the motor give rise to a much greater current.With a load,the energy conversion efficiency of the motor can be enhanced by adjusting the stable indexes of the Lévy noises with symmetry breaking.The results of this research are of great significance for opening up BM’s intrinsic physical mechanism and promoting the development of nanotechnology.

Enhancement of motor functional recovery in thoracic spinal cord injury: voluntary wheel running versus forced treadmill exercise

Spinal cord injury necessitates effective rehabilitation strategies, with exercise therapies showing promise in promoting recovery. This study investigated the impact of rehabilitation exercise on functional recovery and morphological changes following thoracic contusive spinal cord injury. After a 7-day recovery period after spinal cord injury, mice were assigned to either a trained group(10 weeks of voluntary running wheel or forced treadmill exercise) or an untrained group. Bi-weekly assessments revealed that the exercise-trained group, particularly the voluntary wheel exercise subgroup, displayed significantly improved locomotor recovery, more plasticity of dopaminergic and serotonin modulation compared with the untrained group. Additionally, exercise interventions led to gait pattern restoration and enhanced transcranial magnetic motor-evoked potentials. Despite consistent injury areas across groups, exercise training promoted terminal innervation of descending axons. In summary, voluntary wheel exercise shows promise for enhancing outcomes after thoracic contusive spinal cord injury, emphasizing the role of exercise modality in promoting recovery and morphological changes in spinal cord injuries. Our findings will influence future strategies for rehabilitation exercises, restoring functional movement after spinal cord injury.

Integration of bio-inspired limb-like structure damping into motor suspension of high-speed trains to enhance bogie hunting stability

Hunting stability is an important performance criterion in railway vehicles.This study proposes an incorporation of a bio-inspired limb-like structure(LLS)-based nonlinear damping into the motor suspension system for traction units to improve the nonlinear critical speed and hunting stability of high-speed trains(HSTs).Initially,a vibration transmission analysis is conducted on a HST vehicle and a metro vehicle that suffered from hunting motion to explore the effect of different motor suspension systems from on-track tests.Subsequently,a simplified lateral dynamics model of an HST bogie is established to investigate the influence of the motor suspension on the bogie hunting behavior.The bifurcation analysis is applied to optimize the motor suspension parameters for high critical speed.Then,the nonlinear damping of the bio-inspired LLS,which has a positive correlation with the relative displacement,can further improve the modal damping of hunting motion and nonlinear critical speed compared with the linear motor suspension system.Furthermore,a comprehensive numerical model of a high-speed train,considering all nonlinearities,is established to investigate the influence of different types of motor suspension.The simulation results are well consistent with the theoretical analysis.The benefits of employing nonlinear damping of the bio-inspired LLS into the motor suspension of HSTs to enhance bogie hunting stability are thoroughly validated.

Exploring Motor Imagery EEG: Enhanced EEG Microstate Analysis with GMD-Driven Density Canopy Method

The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity.Traditional methods such as Atomic Agglomerative Hierarchical Clustering(AAHC),K-means clustering,Principal Component Analysis(PCA),and Independent Component Analysis(ICA)are limited by a fixed number of microstate maps and insufficient capability in cross-task feature extraction.Tackling these limitations,this study introduces a Global Map Dissimilarity(GMD)-driven density canopy K-means clustering algorithm.This innovative approach autonomously determines the optimal number of EEG microstate topographies and employs Gaussian kernel density estimation alongside the GMD index for dynamic modeling of EEG data.Utilizing this advanced algorithm,the study analyzes the Motor Imagery(MI)dataset from the GigaScience database,GigaDB.The findings reveal six distinct microstates during actual right-hand movement and five microstates across other task conditions,with microstate C showing superior performance in all task states.During imagined movement,microstate A was significantly enhanced.Comparison with existing algorithms indicates a significant improvement in clustering performance by the refined method,with an average Calinski-Harabasz Index(CHI)of 35517.29 and a Davis-Bouldin Index(DBI)average of 2.57.Furthermore,an information-theoretical analysis of the microstate sequences suggests that imagined movement exhibits higher complexity and disorder than actual movement.By utilizing the extracted microstate sequence parameters as features,the improved algorithm achieved a classification accuracy of 98.41%in EEG signal categorization for motor imagery.A performance of 78.183%accuracy was achieved in a four-class motor imagery task on the BCI-IV-2a dataset.These results demonstrate the potential of the advanced algorithm in microstate analysis,offering a more effective tool for a deeper understanding of the spatiotemporal features of EEG signals.

Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control performance.This is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are crucial.The ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is essential.The likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical importance.Long-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be made.The focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation post-failure.This paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past decade.These strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and reestablishment.The paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in FTC.Finally,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.

Cortical activity in patients with high-functioning ischemic stroke during the Purdue Pegboard Test:insights into bimanual coordinated fine motor skills with functional near-infrared spectroscopy

After stroke,even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity,leading to reduced functional independence.Bilateral arm training has been proposed as a promising intervention to address these deficits.However,the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear,limiting the development of more targeted interventions.To address this gap,our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination.Twenty-four high-functioning patients with ischemic stroke(7 women,17 men;mean age 64.75±10.84 years)participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test,which measures unimanual and bimanual finger and hand dexterity.We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks,with bimanual tasks inducing higher cortical activation than the assembly subtask.Importantly,patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks.Notably,the observed neural response patterns varied depending on the specific subtask.In the unaffected hand task,the differences were primarily observed in the ipsilesional hemisphere.In contrast,the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task,respectively.While significant correlations were found between cortical activation and unimanual tasks,no significant correlations were observed with bimanual tasks.This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke,highlighting task-dependent neural responses.The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation.Therefore,incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes.The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.

Review of Thermal Design of SiC Power Module for Motor Drive in Electrical Vehicle Application

In the current vehicle electric propulsion systems,the thermal design of power modules heavily relies on empirical knowledge,making it challenging to effectively optimize irregularly arranged Pinfin structures,thereby limiting their performance.This paper aims to review the underlying mechanisms of how irregularly arranged Pinfins influence the thermal characteristics of power modules and introduce collaborative thermal design with DC bus capacitor and motor.Literature considers chip size,placement,coolant flow direction with the goal of reducing thermal resistance of power modules,minimizing chip junction temperature differentials,and optimizing Pinfin layouts.In the first step,algorithms should efficiently generating numerous unique irregular Pinfin layouts to enhance optimization quality.The second step is to efficiently evaluate Pinfin layouts.Simulation accuracy and speed should be ensured to improve computational efficiency.Finally,to improve overall heat dissipation effectiveness,papers establish models for capacitors,motors,to aid collaborative Pinfin optimization.These research outcomes will provide essential support for future developments in high power density motor drive for vehicles.

Role of End-ring Configuration in Shaping IE4 Induction Motor Performance

The performance characteristics,particularly the starting performance of direct line-fed induction motors,which are mainly influenced by the design of the rotor,are crucial considerations for end-users.It is quite a challenging issue for motor manufacturers to enhance the starting performance of existing mass-produced motors with minimal modifications and expenses.In this paper,a simple and cost-effective method to improve the starting performance of a commercial squirrel-cage induction motor(SCIM)is proposed.The influence of geometric parameters of the end-ring on the performance characteristics,including starting(locked rotor)torque,pull-up and break down torque,starting current,rotor electric parameters,current density,power losses,and efficiency have been comprehensively investigated.It has been revealed that among the other end-ring design parameters,the ring thickness has a significant effect on the performance characteristics.An optimal end-ring thickness is determined,and its performance characteristics have been compared to those of its initial counterpart.Numeric and parametric analyses have been conducted using a 2D time-stepping finite element method(FEM).The FEM results were validated using experimental measurements obtained from an 11 kW SCIM prototype.

Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor

In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

Analysis and Research on Mechanical Stress and Multiobjective Optimization of Synchronous Reluctance Motor

The mechanical strength of the synchronous reluctance motor(SynRM)has always been a great challenge.This paper presents an analysis method for assessing stress equivalence and magnetic bridge stress interaction,along with a multiobjective optimization approach.Considering the complex flux barrier structure and inevitable stress concentration at the bridge,the finite element model suitable for SynRM is established.Initially,a neural network structure with two inputs,one output,and three layers is established.Continuous functions are constructed to enhance accuracy.Additionally,the equivalent stress can be converted into a contour distribution of a three-dimensional stress graph.The contour line distribution illustrates the matching scheme for magnetic bridge lengths under equivalent stress.Moreover,the paper explores the analysis of magnetic bridge interaction stress.The optimization levels corresponding to the length of each magnetic bridge are defined,and each level is analyzed by the finite element method.The Taguchi method is used to determine the specific gravity of the stress source on each magnetic bridge.Based on this,a multiobjective optimization employing the Multiobjective Particle Swarm Optimization(MOPSO)technique is introduced.By taking the rotor magnetic bridge as the design parameter,ten optimization objectives including air-gap flux density,sinusoidal property,average torque,torque ripple,and mechanical stress are optimized.The relationship between the optimization objectives and the design parameters can be obtained based on the response surface method(RSM)to avoid too many experimental samples.The optimized model is compared with the initial model,and the optimized effect is verified.Finally,the temperature distribution of under rated working conditions is analyzed,providing support for addressing thermal stress as mentioned earlier.

Review of Three-phase Soft Switching Inverters and Challenges for Motor Drives

For electric vehicles (EVs),it is necessary to improve endurance mileage by improving the efficiency.There exists a trend towards increasing the system voltage and switching frequency,contributing to improve charging speed and power density.However,this trend poses significant challenges for high-voltage and high-frequency motor controllers,which are plagued by increased switching losses and pronounced switching oscillations as consequences of hard switching.The deployment of soft switching technology presents a viable solution to mitigate these issues.This paper reviews the applications of soft switching technologies for three-phase inverters and classifies them based on distinct characteristics.For each type of inverter,the advantages and disadvantages are evaluated.Then,the paper introduces the research progress and control methods of soft switching inverters (SSIs).Moreover,it presents a comparative analysis among the conventional hard switching inverters (HSIs),an active clamping resonant DC link inverter (ACRDCLI) and an auxiliary resonant commuted pole inverter (ARCPI).Finally,the problems and prospects of soft switching technology applied to motor controllers for EVs are put forward.

Harmonics in the Squirrel Cage Induction Motor Analytic Calculation Part III: Influence on the Torque-speed Characteristic

The harmonics that appear in the squirrel cage asynchronous machine have been discussed in great detail in the literature for a long time. However, the systematization of the phenomenon is still pending, so we made an attempt to fill this gap in the previous parts of our study by elaborating formulas for calculation of parasitic torques. It was a general demand among those who work in this field towards the author to verify his formulas with measurements. In the literature, it seems,only one detailed, purposeful series of measurements has been published so far, the purpose of which was to investigate the effect of the number of rotor slots on the torque-speed characteristic curve of the machine. The main goal of this study is to verify the correctness of the formulas by comparing them with the referred series of measurements. Relying on this, the expected synchronous parasitic torques were developed for the frequently used rotor slot numbers-as a design guide for the engineer.Thus, together with our complete table for radial magnetic pull published in our previous work, the designer has all the principles, data and formulas available for the right number of rotor slots for his given machine and for the drive system. This brings this series of papers to an end.

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor(PMSM)speed control systems with conventional linear active disturbance rejection control(CLADRC)strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances.In order to address these issues,this paper proposes an improved two-degree-of-freedom LADRC(TDOF-LADRC)strategy,which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning.PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately.Moreover,to evaluate the control performance of the TDOF-LADRC strategy,its stability is proven,and the influence of each controller parameter on the system control performance is analyzed.Based on it,a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances.Finally,experiments are performed on a 750 W PMSM experimental platform,and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

Model-free Speed Control of Single-phase Flux Switching Motor with an Asymmetrical Rotor

This paper proposes and implements a model-free open-loop iterative learning control(ILC)strategy to realize the speed control of the single-phase flux switching motor(FSM)with an asymmetrical rotor.Base on the proposed winding control method,the asymmetrical rotor enables the motor to generate continuous positive torque for positive rotation,and relatively small resistance torque for negative rotation.An initial iteration coefficient and variable iteration coefficient optimized scheme was proposed based on the characteristics of the hardware circuit,thereby forming the model-free strategy.A series of prototype experiments was carried out.Experimental results verify the effectiveness and practicability of the proposed ILC strategy.