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.

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.

Liquid Subcutaneous Levodopa-Carbidopa ND0612 Effects on Motor Symptoms in Individuals with Parkinson’s Disease: A Systematic Review and Meta-Analysis

Objective: In the manuscript titled “Liquid subcutaneous Levodopa-Carbidopa ND0612 effects on motor symptoms in individuals with Parkinson’s Disease: A systematic review and meta-analysis”, the objective was to conduct a systematic review with meta-analysis to investigate the effects ND0612 24-hour dosing regimen has on motor symptoms in individuals with Parkinson’s Disease (PD). Introduction: ND0612 is a novel minimally invasive continuous subcutaneous delivery system of liquid Levodopa-Carbidopa being investigated for the treatment of PD in individuals experiencing motor symptoms. Methods: A systematic literature search was conducted in PubMed, Cochrane, and EBSCO databases to identify randomized controlled trials investigating the effects of ND0612 on motor symptoms in individuals with PD. Outcomes included the Unified Parkinson’s Disease Rating Scale (UPDRS) Part II and Part III scores. Methodological quality was assessed using the Cochrane Grading of Recommendations Assessment, Development, and Evaluation approach. Meta-analysis was performed using a random effects model with the DerSimonian and Laird method to estimate the effects of the ND0612 24-hour dosing regimen on UPDRS Part II and Part III scores. Results: Three studies were included in our review. There were statistically significant reductions in UPDRS Part II scores (mean difference (MD) −3.299;95% confidence interval (CI) −3.438, −3.159) and in UPDRS Part III scores (MD −12.695;95% CI −24.428, −0.962) in the ND0612 24-hour dosing regimen. Results were based on very low certainty of evidence. Conclusion: Based on very low certainty evidence, the ND0612 24-hour dosing regimen is effective at improving motor symptoms in individuals with PD. Our findings suggest that ND0612 is more effective at improving UPDRS Part II and Part III scores in individuals with PD than other pharmacological and non-pharmacological treatments, warranting further study.

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.

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.

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

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.

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.

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.

Effect of VOJTA Therapy on Gross Motor Function in Children with Cerebral Palsy

Objective: To investigate the effect of VOJTA therapy on gross motor function in children with cerebral palsy. Methods: The 86 children with cerebral palsy were all from the First People’s Hospital of Jingzhou City from January 2023-December 2023, and were divided into the control group and the study group with 43 cases according to the principle of voluntariness. Results: In terms of total effective rate of treatment, the gross motor function scale-88 (GMFM-88) was used to evaluate the effective rate before and after treatment, and the effective rate of the study group was higher than that of the control group, and the difference was statistically significant, and the scores of gross motor items of GMFM-88 were better than those of the control group after treatment, and the difference was statistically significant (P 0.05). Conclusion: The application of VOJTA therapy in the treatment of children with cerebral palsy can not only promote the rehabilitation of gross motor function, but also help to improve the treatment effect, and the earlier the treatment, the better.

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.

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.

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.

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.

Application of sensory and motor training in AIDET communication mode in patients after knee arthroplasty

BACKGROUND Patients with knee arthroplasty often have problems such as slow recovery of knee function,which may cause negative emotions and affect their postoperative rehabilitation.The application of sensory and motor training in the Acknowledge,Introduce,Duration,Evaluation,Thank You(AIDET)communication mode in patients after knee arthroplasty can provide reference for the selection of postoperative rehabilitation training measures.AIM To explore the sensory and motor training effects in AIDET communication mode on knee function recovery and resilience of patients after knee arthroplasty.METHODS One hundred patients who underwent knee arthroplasty at our hospital between January 2022 and January 2024 were randomly divided into two groups.The control group(n=50)received routine rehabilitation training.In the observation group(n=50),the AIDET communication mode was used to perform sensory and motor training,in addition to routine rehabilitation training.The rehabilitation training was administered for 8 weeks.After surgery,knee function,balance ability,walking ability,proprioception,and resilience were compared between the two groups.RESULTS The New York Hospital for Special Surgery knee scores of the observation group at the time of discharge and 8 weeks after intervention were(65.23±6.84,84.53±5.27),which was higher than those of the control group(61.03±7.15,74.92±6.52)(P<0.05).The balance ability of the observation group at the time of discharge and 8 weeks after the intervention was higher than that of the control group,the time of time up to go test was shorter than that of the control group,and proprioceptive function was higher than that of the control group(P<0.05).The resilience level in the observation group after the intervention was higher than that in the control group(P<0.05).CONCLUSION Sensory and motor training in AIDET communication mode promotes knee function recovery of patients after knee arthroplasty,improves their limb walking ability and balance function,and increases their resilience level.

Airgap-harmonic-oriented Partitioned Design Method of PMV Motor with Improved Torque Performances

Here,we introduce a partitioned design method that is oriented toward airgap harmonic for permanent magnet vernier(PMV)motors.The method proposes the utilization of airgap flux harmonics as an effective bridge between the torque design region and the torque performances.To illustrate the efficacy of this method,a partitioned design PMV motor is presented and compared with the initial design.Firstly,the torque design region of the rotor is artfully divided into the torque enhancement region and ripple reduction region.Meanwhile,the main harmonics that generate output torque are chosen and enhanced,optimization.Moreover,the harmonics that generate torque ripple are selected and reduced based on torque harmonics optimization.Finally,the functions of the partitioned PMV motor torque are assessed based on the finite element method.By the purposeful design of these two regions,the output torque is strengthened while torque ripple is inhibited effectively,verifying the effectiveness and reasonability of the proposed design method.

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.

Research on motor rotation anomaly detection based on improved VMD algorithm

Purpose–The electromechanical brake system is leading the latest development trend in railway braking technology.The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder.The tolerance leads to imprecise brake control,so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system.This paper aims to present improved variational mode decomposition(VMD)algorithm,which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.Design/methodology/approach–The VMD algorithm plays a pivotal role in the preliminary phase,employing mode decomposition techniques to decompose the motor speed signals.Afterward,the error energy algorithm precision is utilized to extract abnormal features,leveraging the practical intrinsic mode functions,eliminating extraneous noise and enhancing the signal’s fidelity.This refined signal then becomes the basis for fault analysis.In the analytical step,the cepstrum is employed to calculate the formant and envelope of the reconstructed signal.By scrutinizing the formant and envelope,the fault point within the electromechanical brake system is precisely identified,contributing to a sophisticated and accurate fault diagnosis.Findings–This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake(EMB)motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction.The signal is reconstructed according to the effective intrinsic mode functions(IMFS)component of removing noise,and the formant and envelope are calculated by cepstrum to locate the fault point.Experiments show that the empirical mode decomposition(EMD)algorithm can effectively decompose the original speed signal.After feature extraction,signal enhancement and fault identification,the motor mechanical fault point can be accurately located.This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.Originality/value–By using this improved VMD algorithm,the electromechanical brake system can precisely identify the rotational anomaly of the motor.This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled.Compared with the conventional motor diagnosis method,this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs.Moreover,the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

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.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.