Time-Domain Analysis of Body Freedom Flutter Based on 6DOF Equation

The reduced weight and improved efficiency of modern aeronautical structures result in a decreasing separation of frequency ranges of rigid and elastic modes.Particularly,a high-aspect-ratio flexible flying wing is prone to body freedomflutter(BFF),which is a result of coupling of the rigid body short-periodmodewith 1st wing bendingmode.Accurate prediction of the BFF characteristics is helpful to reflect the attitude changes of the vehicle intuitively and design the active flutter suppression control law.Instead of using the rigid body mode,this work simulates the rigid bodymotion of the model by using the six-degree-of-freedom(6DOF)equation.A dynamicmesh generation strategy particularly suitable for BFF simulation of free flying aircraft is developed.An accurate Computational Fluid Dynamics/Computational Structural Dynamics/six-degree-of-freedom equation(CFD/CSD/6DOF)-based BFF prediction method is proposed.Firstly,the time-domain CFD/CSD method is used to calculate the static equilibrium state of the model.Based on this state,the CFD/CSD/6DOF equation is solved in time domain to evaluate the structural response of themodel.Then combinedwith the variable stiffnessmethod,the critical flutter point of the model is obtained.This method is applied to the BFF calculation of a flyingwing model.The calculation results of the BFF characteristics of the model agree well with those fromthe modalmethod andNastran software.Finally,the method is used to analyze the influence factors of BFF.The analysis results show that the flutter speed can be improved by either releasing plunge constraint or moving the center ofmass forward or increasing the pitch inertia.

Brillouin optical time-domain analysis for geotechnical monitoring

In this paper, we show some recent experimental applications of Brillouin optical time-domain analysis （BOTDA） based sensors for geotechnical monitoring. In particular, how these sensors can be applied to detecting early movements of soil slopes by the direct embedding of suitable fiber cables in the ground is presented. Furthermore, the same technology can be used to realize innovative inclinometers, as well as smart foundation anchors.

Adsorption and Transfer Properties for Toluene and pDichlorobenzene in Dense CO_2/Silica Gel Packed Bed System by Moment Method and Time-Domain Analysis

Based on chromatographic theory, the moment method and the time-domain fitting analysis were applied to measure and evaluate the adsorption equilibrium constant and mass transfer properties (axial dispersion coefficient and effective intra-particle diffusivity) for toluene and p-dichlorobenzene on silica gel adsorbent in the subcritical and supercritical CO2. An apparatus based on supercritical fluid chromatography was established and the experiments were performed at temperatures of 298.15-318.15 K and pressures of 7.5-17.8 MPa. The two methods have been compared. The results show that for the systems studied here the moment method can give reasonable values for both adsorption equilibrium constant and mass transfer properties, but the time-domain analysis only can obtain the adsorption equilibrium constant. The dependence of adsorption equilibrium constant and mass transfer properties on temperature and pressure was investigated.

Time-Domain Analysis of Underground Station-Layered Soil Interaction Based on High-Order Doubly Asymptotic Transmitting Boundary

Based on the modified scale boundary finite element method and continued fraction solution,a high-order doubly asymptotic transmitting boundary(DATB)is derived and extended to the simulation of vector wave propagation in complex layered soils.The high-order DATB converges rapidly to the exact solution throughout the entire frequency range and its formulation is local in the time domain,possessing high accuracy and good efficiency.Combining with finite element method,a coupled model is constructed for time-domain analysis of underground station-layered soil interaction.The coupled model is divided into the near and far field by the truncated boundary,of which the near field is modelled by FEM while the far field is modelled by the high-order DATB.The coupled model is implemented in an open source finite element software,OpenSees,in which the DATB is employed as a super element.Numerical examples demonstrate that results of the coupled model are stable,accurate and efficient compared with those of the extended mesh model and the viscous-spring boundary model.Besides,it has also shown the fitness for long-time seismic response analysis of underground station-layered soil interaction.Therefore,it is believed that the coupled model could provide a new approach for seismic analysis of underground station-layered soil interaction and could be further developed for engineering.

Time-domain Analysis of FPSO-tanker Responses in Tandem Offloading Operation

Problems experienced during Floating Production, Storage and Offioading （FPSO） tandem offloading operations were investigated. The aim of this research was to improve the reliability of such systems, and it needed a means to assess them. Time-domain simulation and analysis of offioading systems was performed using the multi-body mooring software ARIANE 7.0. Hydrodynamic interaction between the vessels was considered. The responses of the offioading system in different loading cases, different parameters of offioading hawsers and the effects of challenging environmental conditions were calculated. There was a focus on the problems of relative motion between the two bodies and its effects on the intensity of hawser forces. Minimum relative distance, maximum relative headings and maximum tension in the hawsers of offloading systems were obtained by time-domain analysis. The time-domain analysis was effective and comparative study can be used to optimize parameters of the system and extend operating limits.

Time-Domain Analysis of the Relative Motions Between Side-by-Side FLNG and LNGC Under Oblique Waves

Strong hydrodynamic interactions during the side-by-side offloading operation between floating liquefied natural gas(FLNG) and liquefied natural gas carrier(LNGC) can induce high risks of collision. The weather vane effect of a single-point mooring system normally results in the satisfactory hydrodynamic performance of the side-by-side configuration in head seas. Nevertheless, the changes in wave directions in real sea conditions can significantly influence the relative motions. This article studies the relative motions of the side-by-side system by using the theoretical analysis method and the numerical calculation method. Based on the three-dimensional potential theory modified by artificial damping-lid method, the frequency-domain hydrodynamic coefficients can be improved to calculate the retardation functions for the multi-body problem. An in-house code is then developed to perform the time-domain simulation of two vessels, through which the relative motions are subsequently obtained. A range of oblique waves are chosen for the extensive calculation of relative motions between the two vessels, which are further analyzed in terms of the phase shift of motion responses induced by specific resonant wave patterns. Investigation results show that wave directions have a significant influence on the relative sway, roll, and yaw motions. Under the circumstance that the absolute phase shift between the roll motions of two vessels approaches 180°, stronger relative motions are induced when LNGC is on the weather side.Moreover, the gap water resonances at high frequencies tend to cause the dangerous opposed oscillation of two vessels in the sway and yaw modes, whereas FLNG reduces the gap water resonances and relative motions when located on the weather side.

Text-Image Feature Fine-Grained Learning for Joint Multimodal Aspect-Based Sentiment Analysis

Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features.Given this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for JMASA.First,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect terms.Then,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature learning.Thereby,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and enhanced.Experiments on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.

Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.

Research status and prospects of the fractal analysis of metal material surfaces and interfaces

As a mathematical analysis method,fractal analysis can be used to quantitatively describe irregular shapes with self-similar or self-affine properties.Fractal analysis has been used to characterize the shapes of metal materials at various scales and dimensions.Conventional methods make it difficult to quantitatively describe the relationship between the regular characteristics and properties of metal material surfaces and interfaces.However,fractal analysis can be used to quantitatively describe the shape characteristics of metal materials and to establish the quantitative relationships between the shape characteristics and various properties of metal materials.From the perspective of two-dimensional planes and three-dimensional curved surfaces,this paper reviews the current research status of the fractal analysis of metal precipitate interfaces,metal grain boundary interfaces,metal-deposited film surfaces,metal fracture surfaces,metal machined surfaces,and metal wear surfaces.The relationship between the fractal dimensions and properties of metal material surfaces and interfaces is summarized.Starting from three perspectives of fractal analysis,namely,research scope,image acquisition methods,and calculation methods,this paper identifies the direction of research on fractal analysis of metal material surfaces and interfaces that need to be developed.It is believed that revealing the deep influence mechanism between the fractal dimensions and properties of metal material surfaces and interfaces will be the key research direction of the fractal analysis of metal materials in the future.

Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

Antioxidant and lipoxygenase inhibitory properties of a novel flavonoid from Pistacia chinensis Bunge and its molecular docking analysis

Background:Pistacia chinensis Bunge has been traditionally used to manage various conditions,including asthma,pain,inflammation,hepatoprotection,and diabetes.The study was conducted to investigate the antioxidant and anti-lipoxygenase(LOX)properties of the isolated compound 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one from Pistacia chinensis.Methods:LOX assay and antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl(DPPH)assay were performed.Molecular docking studies were conducted using a molecular operating environment.Results:The LOX assay revealed significant inhibitory effects at 0.2µM concentration,with an IC50 value of 37.80µM.The antioxidant effect demonstrated dose-dependency across 5 to 100µg/mL concentrations,reaching 93.09%at 100µg/mL,comparable to ascorbic acid’s 95.43%effect.Molecular docking studies highlighted strong interactions with the lipoxygenase enzyme,presenting an excellent docking score of-10.98 kcal/mol.Conclusion:These findings provide valuable insights into Pistacia chinensis’chemical components and biological effects,reinforcing its traditional medicinal applications.

Optimizing Fine-Tuning in Quantized Language Models:An In-Depth Analysis of Key Variables

Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.

Fatigue Strength Analysis of Dissimilar Aluminum Alloy TIG Welds

The constant amplitude loading fatigue tests were carried out on the 6061/7075 aluminum alloy TIG fillet welded lap specimens in this study,and the weld seam cross-section hardness was measured.The experimental results show that most specimens mainly failed at the 7075 side weld toes even though the base material tensile strength of 7075 is higher than that of 6061.The maximum stress-strain concentration in the two finite element models is located at the 7075 side weld toe,which is basically consistent with the actual fracture location.The weld zone on the 7075 side experiences severe material softening,with a large gradient.However,the Vickers hardness value on the 6061 side negligibly changes and fluctuates around 70 HV.No obvious defects are found on the fatigue fracture,but a large number of secondary cracks appear.Cracks germinate from the weld toe and propagate in the direction of the plate thickness.Weld reinforcement has a serious impact on fatigue life.Fatigue life will decrease exponentially as the weld reinforcement increases under low stress.It is found that the notch stress method can give a better fatigue life prediction for TIG weldments,and the errors of the predicted results are within the range of two factors,while the prediction accuracy decreases under low stress.The equivalent structural stress method can also be used for fatigue life prediction of TIG weldments,but the errors of prediction results are within the range of three factors,and the accuracy decreases under high stress.

Enhancing Solar Photovoltaic Efficiency:A Computational Fluid Dynamics Analysis

The growing need for sustainable energy solutions,driven by rising energy shortages,environmental concerns,and the depletion of conventional energy sources,has led to a significant focus on renewable energy.Solar energy,among the various renewable sources,is particularly appealing due to its abundant availability.However,the efficiency of commercial solar photovoltaic(PV)modules is hindered by several factors,notably their conversion efficiency,which averages around 19%.This efficiency can further decline to 10%–16%due to temperature increases during peak sunlight hours.This study investigates the cooling of PV modules by applying water to their front surface through Computational fluid dynamics(CFD).The study aimed to determine the optimal conditions for cooling the PV module by analyzing the interplay between water film thickness,Reynolds number,and their effects on temperature reduction and heat transfer.The CFD analysis revealed that the most effective cooling condition occurred with a 5 mm thick water film and a Reynolds number of 10.These specific parameters were found to maximize the heat transfer and temperature reduction efficiency.This finding is crucial for the development of practical and efficient cooling systems for PV modules,potentially leading to improved performance and longevity of solar panels.Alternative cooling fluids or advanced cooling techniques that might offer even better efficiency or practical benefits.

Multilevel analysis of the central-peripheral-target organ pathway:contributing to recovery after peripheral nerve injury

Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.

Time-domain analysis methodology for large-scale RLC circuits and its applications

With soaring work frequency and decreasing feature sizes, VLSI circuits with RLC parasitic components are more like analog circuits and should be carefully analyzed in physical design. However, the number of extracted RLC components is typically too large to be analyzed efficiently by using present analog circuit simulators like SPICE. In order to speedup the simulations without error penalty, this paper proposes a novel methodology to compress the time-descritized circuits resulted from numerical integration approximation at every time step. The main contribution of the methodology is the efficient structure-level compression of DC circuits containing many current sources, which is an important complement to present circuit analysis theory. The methodology consists of the following parts： 1） An approach is proposed to delete all intermediate nodes of RL branches. 2） An efficient approach is proposed to compress and back-solve parallel and serial branches so that it is error-free and of linear complexity to analyze circuits of tree topology. 3） The Y to πtransformation method is used to error-free reduce and back-solve the intermediate nodes of ladder circuits with the linear complexity. Thus, the whole simulation method is very accurate and of linear complexity to analyze circuits of chain topology. Based on the methodology, we propose several novel algorithms for efficiently solving RLC-model transient power/ground （P/G） networks. Among them, EQU-ADI algorithm of linear-complexity is proposed to solve RLC P/G networks with mesh-tree or mesh-chain topologies. Experimental results show that the proposed method is at least two orders of magnitude faster than SPICE while it can scale linearly in both time- and memory-complexity to solve very large P/G networks.

Dynamic Coupling Analysis of Semisubmersible Platform Float-over Method for Docking Case

In this paper,the multi-body coupled dynamic characteristics of a semisubmersible platform and an HYSY 229 barge were investigated.First,coupled hydrodynamic analysis of the HYSY 229 barge and the semisubmersible platform was performed.Relevant hydrodynamic parameters were obtained using the retardation function method of three-dimensional frequency-domain potential flow theory.The results of the hydrodynamic analysis were highly consistent with the test findings,verifying the accuracy of the multifloating hydrodynamic coupling analysis,and key hydrodynamic parameters were solved for different water depths and the coupling effect.According to the obtained results,the hydrodynamic influence was the largest in shallow waters when the coupling effect was considered.Furthermore,the coupled motion equation combined with viscous damping,fender system,and mooring system was established,and the hydrodynamics,floating body motion,and dynamic response of the fender system were analyzed.Motion analysis revealed good agreement among the surge,sway,and yaw motions of the two floating bodies.However,when the wave period reached 10 s,the motion of the two floating bodies showed severe shock,and a relative motion was also observed.Therefore,excessive constraints should be added between the two floating bodies during construction to ensure construction safety.The numerical analysis and model test results of the semisubmersible platform and HYSY 229 barge at a water depth of 42 m and sea conditions of 0°,45°,and 90° were in good agreement,and the error was less than 5%.The maximum movement of the HYSY 229 barge reached 2.61 m in the sway direction,whereas that of the semisubmersible platform was 2.11 m.During construction,excessive constraints should be added between the two floating bodies to limit their relative movement and ensure construction safety.

Solution and Analysis of Chatter Stability for End Milling in the Time-domain

In this paper, the instantaneous undeformed chip thickness is modeled to include the dynamic modulation caused by the tool vibration while the dynamic regenerative effects are taken into account. The numerical method is used to solve the differential equations goveming the dynamics of the milling system. Several chatter detection criteria are applied synthetically to the simulated signals and the stability diagram is obtained in time-domain. The simulation results in time-domain show a good agreement with the analytical prediction, which is validated by the cutting experiments. By simulating the chatter stability lobes in the time-domain and analyzing the influences of different spindle speeds on the vibration amplitudes of the tool under a Fixed chip-load condition, conclusions could be drawn as follows： In rough milling, higher machining efficiency can be achieved by selecting a spindle speed corresponding to the axial depth of cut in accordance with the simulated chatter stability lobes, and in Fmish milling, lower surface roughness can be achieved by selecting a spindle speed well beyond the resonant frequency of machining system.

Time-domain analysis for vibration and sound radiation of submerged spherical shell excited by force

The vibration and sound radiation of a submerged spherical shell are studied in the time-domain by Laplace transform method, where a CW pulse force acts at the apex of the shell. The numerical results for the case of long pulse show that the different vibrational modes and the resonant or beat radiated sound are excited for different carrier-frequencies, but litle sound is radiated for some vibrational modes. For the case of short pulse the waveforms of the pulse become widened and deformed, when the pulse propagates between apexes of the shell. Then, the Doubly Asymptotic Approximations (DAA2) and Kirchhoff's Retarded Potential Formulate (KRPF)are used to solve the same problem. It is shown that the results of DAA2 and KRPF method have a good agreement with the results of Laplace transform method.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).