Efficient Intelligent E-Learning Behavior-Based Analytics of Student’s Performance Using Deep Forest Model

E-learning behavior data indicates several students’activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures.This article proposes a new analytics systemto support academic evaluation for students via e-learning activities to overcome the challenges faced by traditional learning environments.The proposed e-learning analytics system includes a new deep forest model.It consists of multistage cascade random forests with minimal hyperparameters compared to traditional deep neural networks.The developed forest model can analyze each student’s activities during the use of an e-learning platform to give accurate expectations of the student’s performance before ending the semester and/or the final exam.Experiments have been conducted on the Open University Learning Analytics Dataset(OULAD)of 32,593 students.Our proposed deep model showed a competitive accuracy score of 98.0%compared to artificial intelligence-based models,such as ConvolutionalNeuralNetwork(CNN)and Long Short-TermMemory(LSTM)in previous studies.That allows academic advisors to support expected failed students significantly and improve their academic level at the right time.Consequently,the proposed analytics system can enhance the quality of educational services for students in an innovative e-learning framework.

A Stacking Machine Learning Model for Student Performance Prediction Based on Class Activities in E-Learning

After the spread of COVID-19,e-learning systems have become crucial tools in educational systems worldwide,spanning all levels of education.This widespread use of e-learning platforms has resulted in the accumulation of vast amounts of valuable data,making it an attractive resource for predicting student performance.In this study,we aimed to predict student performance based on the analysis of data collected from the OULAD and Deeds datasets.The stacking method was employed for modeling in this research.The proposed model utilized weak learners,including nearest neighbor,decision tree,random forest,enhanced gradient,simple Bayes,and logistic regression algorithms.After a trial-and-error process,the logistic regression algorithm was selected as the final learner for the proposed model.The results of experiments with the above algorithms are reported separately for the pass and fail classes.The findings indicate that the accuracy of the proposed model on the OULAD dataset reached 98%.Overall,the proposed method improved accuracy by 4%on the OULAD dataset.

E-learning在医学教育领域内的实践与研究

科学技术与医学教育的发展,对医学教育的过程及途径提出新要求。电子学习(E-learning)作为一种新型教学方式,早已在教育、培训等领域广泛应用,尤其是在国外。在国内医学教育领域中,E-learning也得到迅速发展,并发挥积极作用。随着这种应用趋势的展开,不少学者对此进行相关研究。本文在对E-learning方式进行解读的基础上,追溯其发展历程与在医学教育领域内的应用现状,对相关的国内外研究资料进行回顾,为E-learning在国内医学教育的实践研究提供建设性启示。

基于E-learning的翻转课堂模式在消化系统疾病实习教学中的应用效果

目的 探讨基于E-learning的翻转课堂模式在消化系统疾病实习教学中的应用效果。方法 选取2021年8月至2022年7月在新疆医科大学第一临床医学院就读的200名临床医学专业学生,采用随机数字表法分为研究组(100名)与对照组(100名)。研究组采用基于E-learning的翻转课堂模式教学,对照组实施传统教学模式教学。比较两组学生自我评价、教师对学生能力评价以及理论考核和临床操作考核成绩。结果 研究组学生学习兴趣、学习效率、学习信心、总体满意度的自我评价均高于对照组(P均<0.05);带教教师对研究组学生自主学习能力、团队协作能力、临床思维能力、临床技能能力评价均高于对照组(P均<0.05);研究组学生理论考核和临床操作考核成绩均高于对照组(P均<0.05)。结论 基于E-learning的翻转课堂模式可有效培养学生临床思维和操作能力,提升消化系统疾病实习教学效率及教学效果。

Influence of heat treatment on microstructure,mechanical and corrosion behavior of WE43 alloy fabricated by laser-beam powder bed fusion

Magnesium(Mg)alloys are considered to be a new generation of revolutionary medical metals.Laser-beam powder bed fusion(PBF-LB)is suitable for fabricating metal implants withpersonalized and complicated structures.However,the as-built part usually exhibits undesirable microstructure and unsatisfactory performance.In this work,WE43 parts were firstly fabricated by PBF-LB and then subjected to heat treatment.Although a high densification rate of 99.91%was achieved using suitable processes,the as-built parts exhibited anisotropic and layeredmicrostructure with heterogeneously precipitated Nd-rich intermetallic.After heat treatment,fine and nano-scaled Mg24Y5particles were precipitated.Meanwhile,theα-Mg grainsunderwent recrystallization and turned coarsened slightly,which effectively weakened thetexture intensity and reduced the anisotropy.As a consequence,the yield strength and ultimate tensile strength were significantly improved to(250.2±3.5)MPa and(312±3.7)MPa,respectively,while the elongation was still maintained at a high level of 15.2%.Furthermore,the homogenized microstructure reduced the tendency of localized corrosion and favoredthe development of uniform passivation film.Thus,the degradation rate of WE43 parts was decreased by an order of magnitude.Besides,in-vitro cell experiments proved their favorable biocompatibility.

Integrated ribosome and proteome analyses reveal insights into sevoflurane-induced long-term social behavior and cognitive dysfunctions through ADNP inhibition in neonatal mice

A growing number of studies have demonstrated that repeated exposure to sevoflurane during development results in persistent social abnormalities and cognitive impairment.Davunetide,an active fragment of the activity-dependent neuroprotective protein(ADNP),has been implicated in social and cognitive protection.However,the potential of davunetide to attenuate social deficits following sevoflurane exposure and the underlying developmental mechanisms remain poorly understood.In this study,ribosome and proteome profiles were analyzed to investigate the molecular basis of sevoflurane-induced social deficits in neonatal mice.The neuropathological basis was also explored using Golgi staining,morphological analysis,western blotting,electrophysiological analysis,and behavioral analysis.Results indicated that ADNP was significantly down-regulated following developmental exposure to sevoflurane.In adulthood,anterior cingulate cortex(ACC)neurons exposed to sevoflurane exhibited a decrease in dendrite number,total dendrite length,and spine density.Furthermore,the expression levels of Homer,PSD95,synaptophysin,and vglut2 were significantly reduced in the sevoflurane group.Patch-clamp recordings indicated reductions in both the frequency and amplitude of miniature excitatory postsynaptic currents(mEPSCs).Notably,davunetide significantly ameliorated the synaptic defects,social behavior deficits,and cognitive impairments induced by sevoflurane.Mechanistic analysis revealed that loss of ADNP led to dysregulation of Ca^(2+)activity via the Wnt/β-catenin signaling,resulting in decreased expression of synaptic proteins.Suppression of Wnt signaling was restored in the davunetide-treated group.Thus,ADNP was identified as a promising therapeutic target for the prevention and treatment of neurodevelopmental toxicity caused by general anesthetics.This study provides important insights into the mechanisms underlying social and cognitive disturbances caused by sevoflurane exposure in neonatal mice and elucidates the regulatory pathways involved.

Association of preschool children behavior and emotional problems with the parenting behavior of both parents

BACKGROUND Parental behaviors are key in shaping children’s psychological and behavioral development,crucial for early identification and prevention of mental health issues,reducing psychological trauma in childhood.AIM To investigate the relationship between parenting behaviors and behavioral and emotional issues in preschool children.METHODS From October 2017 to May 2018,7 kindergartens in Ma’anshan City were selected to conduct a parent self-filled questionnaire-Health Development Survey of Preschool Children.Children’s Strength and Difficulties Questionnaire(Parent Version)was applied to measures the children’s behavioral and emotional performance.Parenting behavior was evaluated using the Parental Behavior Inventory.Binomial logistic regression model was used to analyze the association between the detection rate of preschool children’s behavior and emotional problems and their parenting behaviors.RESULTS High level of parental support/participation was negatively correlated with conduct problems,abnormal hyperactivity,abnormal total difficulty scores and abnormal prosocial behavior problems.High level of maternal support/participation was negatively correlated with abnormal emotional symptoms and abnormal peer interaction in children.High level of parental hostility/coercion was positively correlated with abnormal emotional symptoms,abnormal conduct problems,abnormal hyperactivity,abnormal peer interaction,and abnormal total difficulty scores in children(all P<0.05).Moreover,paternal parenting behaviors had similarly effects on behavior and emotional problems of preschool children compared with maternal parenting behaviors(all P>0.05),after calculating ratio of odds ratio values.CONCLUSION Our study found that parenting behaviors are associated with behavioral and emotional issues in preschool children.Overall,the more supportive or involved the parents are,the fewer behavioral and emotional problems the children experience;conversely,the more hostile or controlling the parents are,the more behavioral and emotional problems the children face.Moreover,the impact of fathers’parenting behaviors on preschool children’s behavior and emotions is no less significant than that of mothers’parenting behaviors.

Shear behavior of single-joint bolted sandstone subjected to dryewet cycles:Experimental and analytical approaches

A series of direct shear tests under constant normal loading conditions were carried out on specimens of bolted sandstone single-joint treated with different numbers of dryewet cycles.The experimental results show that the peak shear strength and shear stiffness of bolted sandstone joints were significantly reduced after 12 dryewet cycles.The decrease in the shear strength of rough joints is more significant than that of flat joints.Due to the decrease in the strength of the surrounding rock,the deformation characteristics of the bolts are significantly affected by the number of dryewet cycles performed.With an increase in the number of dryewet cycles,the plastic hinge length of the bolt gradually increases,resulting in an increase in the corresponding shear displacement when the bolt breaks.Compared with the tensileeshear failure mode of the bolts in flat joints,the tensileebending failure mode arises for bolts in rough joints.A shear curve model describing the whole process of bolted rock joints is established based on the deterioration of rock mechanical parameters caused by dry‒wet cycles.The model proposed considers the change in the friction angle of the joint surface with the shear displacement,which is applied to the derivation of the model by introducing the dynamic evolutionary friction angle parameter.The reasonably good agreement between a predicted curve and the corresponding experimental curve indicates that this method can effectively predict the shear strength of a bolted rock joint involving rough joint under dryewet cycling conditions.

Microstructures and micromechanical behaviors of high -entropy alloys investigated by synchrotron X-ray and neutron diffraction techniques: A review

High-entropy alloys(HEAs)possess outstanding features such as corrosion resistance,irradiation resistance,and good mechan-ical properties.A few HEAs have found applications in the fields of aerospace and defense.Extensive studies on the deformation mech-anisms of HEAs can guide microstructure control and toughness design,which is vital for understanding and studying state-of-the-art structural materials.Synchrotron X-ray and neutron diffraction are necessary techniques for materials science research,especially for in situ coupling of physical/chemical fields and for resolving macro/microcrystallographic information on materials.Recently,several re-searchers have applied synchrotron X-ray and neutron diffraction methods to study the deformation mechanisms,phase transformations,stress behaviors,and in situ processes of HEAs,such as variable-temperature,high-pressure,and hydrogenation processes.In this review,the principles and development of synchrotron X-ray and neutron diffraction are presented,and their applications in the deformation mechanisms of HEAs are discussed.The factors that influence the deformation mechanisms of HEAs are also outlined.This review fo-cuses on the microstructures and micromechanical behaviors during tension/compression or creep/fatigue deformation and the application of synchrotron X-ray and neutron diffraction methods to the characterization of dislocations,stacking faults,twins,phases,and intergrain/interphase stress changes.Perspectives on future developments of synchrotron X-ray and neutron diffraction and on research directions on the deformation mechanisms of novel metals are discussed.

PCDH17 restricts dendritic spine morphogenesis by regulating ROCK2-dependent control of the actin cytoskeleton,modulating emotional behavior

Proper regulation of synapse formation and elimination is critical for establishing mature neuronal circuits and maintaining brain function.Synaptic abnormalities,such as defects in the density and morphology of postsynaptic dendritic spines,underlie the pathology of various neuropsychiatric disorders.Protocadherin 17(PCDH17)is associated with major mood disorders,including bipolar disorder and depression.However,the molecular mechanisms by which PCDH17 regulates spine number,morphology,and behavior remain elusive.In this study,we found that PCDH17 functions at postsynaptic sites,restricting the number and size of dendritic spines in excitatory neurons.Selective overexpression of PCDH17 in the ventral hippocampal CA1 results in spine loss and anxiety-and depression-like behaviors in mice.Mechanistically,PCDH17 interacts with actin-relevant proteins and regulates actin filament(F-actin)organization.Specifically,PCDH17 binds to ROCK2,increasing its expression and subsequently enhancing the activity of downstream targets such as LIMK1 and the phosphorylation of cofilin serine-3(Ser3).Inhibition of ROCK2 activity with belumosudil(KD025)ameliorates the defective F-actin organization and spine structure induced by PCDH17 overexpression,suggesting that ROCK2 mediates the effects of PCDH17 on F-actin content and spine development.Hence,these findings reveal a novel mechanism by which PCDH17 regulates synapse development and behavior,providing pathological insights into the neurobiological basis of mood disorders.

Snap-through behaviors and nonlinear vibrations of a bistable composite laminated cantilever shell:an experimental and numerical study

The snap-through behaviors and nonlinear vibrations are investigated for a bistable composite laminated cantilever shell subjected to transversal foundation excitation based on experimental and theoretical approaches.An improved experimental specimen is designed in order to satisfy the cantilever support boundary condition,which is composed of an asymmetric region and a symmetric region.The symmetric region of the experimental specimen is entirely clamped,which is rigidly connected to an electromagnetic shaker,while the asymmetric region remains free of constraint.Different motion paths are realized for the bistable cantilever shell by changing the input signal levels of the electromagnetic shaker,and the displacement responses of the shell are collected by the laser displacement sensors.The numerical simulation is conducted based on the established theoretical model of the bistable composite laminated cantilever shell,and an off-axis three-dimensional dynamic snap-through domain is obtained.The numerical solutions are in good agreement with the experimental results.The nonlinear stiffness characteristics,dynamic snap-through domain,and chaos and bifurcation behaviors of the shell are quantitatively analyzed.Due to the asymmetry of the boundary condition and the shell,the upper stable-state of the shell exhibits an obvious soft spring stiffness characteristic,and the lower stable-state shows a linear stiffness characteristic of the shell.

Impact of parenting styles on preschoolers’behaviors

In this editorial,I comment on the article“Association of preschool children behavior and emotional problems with the parenting behavior of both parents”which was published in the latest issue of“World Journal of Clinical Cases”that demonstrates the prevalence of behavioral disorders in preschool children.Therefore I am focused on parenting which is the most effective factor shown to affect the development and continuity of these behaviors.The management of child behavior problems is crucial.Children in early ages,especially preschoolers who are in the first 5 years of life,are influenced by dramatic changes in various aspects of development,such as social,emotional,and physical.Also,children experience many changes linked to different developmental tasks,such as discovering themselves,getting new friendships,and adapting to a new environment.In this period,parents have a critical role in supporting child development.If parents do not manage and overcome their child’s misbehavior,it could be transformed into psychosocial problems in adulthood.Parenting is the most powerful predictor in the social development of preschool children.Several studies have shown that to reduce the child’s emotional and behavioral problems,a warm relationship between parents and children is needed.In addition,recent studies have demonstrated significant relationships between family regulation factors and parenting,as well as with child behaviors.

Elastic-viscoplastic behaviors of polymer-blend geocell sheets:Numerical and experimental investigations

Polymer-blend geocell sheets(PBGS)have been developed as substitute materials for manufacturing geocells.Various attempts have been made to test and predict the behaviors of commonly used geogrids,geotextiles,geomembranes,and geocells.However,the elastic-viscoplastic behaviors of novel-developed geocell sheets are still poorly understood.Therefore,this paper investigates the elastic-viscoplastic behaviors of PBGS to gain a comprehensive understanding of their mechanical properties.Furthermore,the tensile load-strain history under various loading conditions is simulated by numerical calculation for widespread utilization.To achieve this goal,monotonic loading tests,short-term creep and stress relaxation tests,and multi-load-path tests(also known as arbitrary loading history tests)are performed using a universal testing machine.The results are simulated using the nonlinear three-component(NLTC)model,which consists of three nonlinear components,i.e.a hypo-elastic component,a nonlinear inviscid component,and a nonlinear viscid component.The experimental and numerical results demonstrate that PBGS exhibit significant elastic-viscoplastic behavior that can be accurately predicted by the NLTC model.Moreover,the tensile strain rates significantly influence the tensile load,with higher strain rates resulting in increased tensile loads and more linear load-strain curves.Also,parametric analysis of the rheological characteristics reveals that the initial tensile strain rates have negligible impact on the results.The rate-sensitivity coefficient of PBGS is approximately 0.163,which falls within the typical range observed in most geosynthetics.

Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments

In recent times,technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between learners.Integrating the Internet of Things(IoT)into education can facilitate the teaching and learning process and expand the context in which students learn.Nevertheless,learning data is very sensitive and must be protected when transmitted over the network or stored in data centers.Moreover,the identity and the authenticity of interacting students,instructors,and staff need to be verified to mitigate the impact of attacks.However,most of the current security and authentication schemes are centralized,relying on trusted third-party cloud servers,to facilitate continuous secure communication.In addition,most of these schemes are resourceintensive;thus,security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being used.In this paper,we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university network.It allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user re-authentication.The proposed architecture was tested using a simulation tool,and measured to evaluate its performance.The simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions(40%),reduce the communication overhead and response time(26%),improve authentication efficiency(27%),and reduce the IoT power consumption(35%)compared to the centralized authentication mechanisms.In addition,the security analysis proves the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the university network.

Comparison of electrochemical behaviors of Ti-5Al-2Sn-4Zr-4Mo-2Cr-1Fe and Ti-6Al-4V titanium alloys in NaNO_(3) solution

The Ti-5Al-2Sn-4Zr-4Mo-2Cr-1Fe(β-CEZ)alloy is considered as a potential structural material in the aviation industry due to its outstanding strength and corrosion resistance.Electrochemical machining(ECM)is an efficient and low-cost technology for manufacturing theβ-CEZ alloy.In ECM,the machining parameter selection and tool design are based on the electrochemical dissolution behavior of the materials.In this study,the electrochemical dissolution behaviors of theβ-CEZ and Ti-6Al-4V(TC4)alloys in NaNO3solution are discussed.The open circuit potential(OCP),Tafel polarization,potentiodynamic polarization,electrochemical impedance spectroscopy(EIS),and current efficiency curves of theβ-CEZ and TC4 alloys are analyzed.The results show that,compared to the TC4 alloy,the passivation film structure is denser and the charge transfer resistance in the dissolution process is greater for theβ-CEZ alloy.Moreover,the dissolved surface morphology of the two titanium-based alloys under different current densities are analyzed.Under low current densities,theβ-CEZ alloy surface comprises dissolution pits and dissolved products,while the TC4 alloy surface comprises a porous honeycomb structure.Under high current densities,the surface waviness of both the alloys improves and the TC4 alloy surface is flatter and smoother than theβ-CEZ alloy surface.Finally,the electrochemical dissolution models ofβ-CEZ and TC4 alloys are proposed.

Real Objects Understanding Using 3D Haptic Virtual Reality for E-Learning Education

In the past two decades,there has been a lot of work on computer vision technology that incorporates many tasks which implement basic filtering to image classification.Themajor research areas of this field include object detection and object recognition.Moreover,wireless communication technologies are presently adopted and they have impacted the way of education that has been changed.There are different phases of changes in the traditional system.Perception of three-dimensional(3D)from two-dimensional(2D)image is one of the demanding tasks.Because human can easily perceive but making 3D using software will take time manually.Firstly,the blackboard has been replaced by projectors and other digital screens so such that people can understand the concept better through visualization.Secondly,the computer labs in schools are now more common than ever.Thirdly,online classes have become a reality.However,transferring to online education or e-learning is not without challenges.Therefore,we propose a method for improving the efficiency of e-learning.Our proposed system consists of twoand-a-half dimensional(2.5D)features extraction using machine learning and image processing.Then,these features are utilized to generate 3D mesh using ellipsoidal deformation method.After that,3D bounding box estimation is applied.Our results show that there is a need to move to 3D virtual reality(VR)with haptic sensors in the field of e-learning for a better understanding of real-world objects.Thus,people will have more information as compared to the traditional or simple online education tools.We compare our result with the ShapeNet dataset to check the accuracy of our proposed method.Our proposed system achieved an accuracy of 90.77%on plane class,85.72%on chair class,and car class have 72.14%.Mean accuracy of our method is 70.89%.

Timing theory integrated nursing combined behavior change integrated theory of nursing on primiparous influence

BACKGROUND The comprehension and utilization of timing theory and behavior change can offer a more extensive and individualized provision of support and treatment alternatives for primipara.This has the potential to enhance the psychological well-being and overall quality of life for primipara,while also furnishing healthcare providers with efficacious interventions to tackle the psychological and physiological obstacles encountered during the stages of pregnancy and postpartum.AIM To explore the effect of timing theory combined with behavior change on selfefficacy,negative emotions and quality of life in patients with primipara.METHODS A total of 80 primipara cases were selected and admitted to our hospital between August 2020 and May 2022.These cases were divided into two groups,namely the observation group and the control group,with 40 cases in each group.The nursing interventions differed between the two groups,with the control group receiving routine nursing and the observation group receiving integrated nursing based on the timing theory and behavior change.The study aimed to compare the pre-and post-nursing scores of Chinese Perceived Stress Scale(CPSS),Edinburgh Postpartum Depression Scale(EPDS),Self-rating Anxiety Scale(SAS),breast milk knowledge,self-efficacy,and SF-36 quality of life in both groups.RESULTS After nursing,the CPSS,EPDS,and SAS scores of the two groups was significantly lower than that before nursing,and the CPSS,EPDS,and SAS scores of the observation group was significantly lower than that of the control group(P=0.002,P=0.011,and P=0.001 respectively).After nursing,the breastfeeding knowledge mastery,selfefficacy,and SF-36 quality of life scores was significantly higher than that before nursing,and the breastfeeding knowledge mastery(P=0.013),self-efficacy(P=0.008),and SF-36 quality of life(P=0.011)scores of the observation group was significantly higher than that of the control group.CONCLUSION The integration of timing theory and behavior change integrated theory has been found to be an effective approach in alleviating negative mood and stress experienced by primipara individuals,while also enhancing their selfefficacy and overall quality of life.This study focuses on the key concepts of timing theory,behavior change,primipara individuals,negative mood,and quality of life.

Student’s Health Exercise Recognition Tool for E-Learning Education

Due to the recently increased requirements of e-learning systems,multiple educational institutes such as kindergarten have transformed their learning towards virtual education.Automated student health exercise is a difficult task but an important one due to the physical education needs especially in young learners.The proposed system focuses on the necessary implementation of student health exercise recognition(SHER)using a modified Quaternion-basedfilter for inertial data refining and data fusion as the pre-processing steps.Further,cleansed data has been segmented using an overlapping windowing approach followed by patterns identification in the form of static and kinematic signal patterns.Furthermore,these patterns have been utilized to extract cues for both patterned signals,which are further optimized using Fisher’s linear discriminant analysis(FLDA)technique.Finally,the physical exercise activities have been categorized using extended Kalmanfilter(EKF)-based neural networks.This system can be implemented in multiple educational establishments including intelligent training systems,virtual mentors,smart simulations,and interactive learning management methods.

A Comparative Study on the Post-Buckling Behavior of Reinforced Thermoplastic Pipes(RTPs)Under External Pressure Considering Progressive Failure

The collapse pressure is a key parameter when RTPs are applied in harsh deep-water environments.To investigate the collapse of RTPs,numerical simulations and hydrostatic pressure tests are conducted.For the numerical simulations,the eigenvalue analysis and Riks analysis are combined,in which the Hashin failure criterion and fracture energy stiffness degradation model are used to simulate the progressive failure of composites,and the“infinite”boundary conditions are applied to eliminate the boundary effects.As for the hydrostatic pressure tests,RTP specimens were placed in a hydrostatic chamber after filled with water.It has been observed that the cross-section of the middle part collapses when it reaches the maximum pressure.The collapse pressure obtained from the numerical simulations agrees well with that in the experiment.Meanwhile,the applicability of NASA SP-8007 formula on the collapse pressure prediction was also discussed.It has a relatively greater difference because of the ignorance of the progressive failure of composites.For the parametric study,it is found that RTPs have much higher first-ply-failure pressure when the winding angles are between 50°and 70°.Besides,the effect of debonding and initial ovality,and the contribution of the liner and coating are also discussed.

Neurophysiological, histological, and behavioral characterization of animal models of distraction spinal cord injury: a systematic review

Distraction spinal cord injury is caused by some degree of distraction or longitudinal tension on the spinal cord and commonly occurs in patients who undergo corrective operation for severe spinal deformity.With the increased degree and duration of distraction,spinal cord injuries become more serious in terms of their neurophysiology,histology,and behavior.Very few studies have been published on the specific characteristics of distraction spinal cord injury.In this study,we systematically review 22 related studies involving animal models of distraction spinal cord injury,focusing particularly on the neurophysiological,histological,and behavioral characteristics of this disease.In addition,we summarize the mechanisms underlying primary and secondary injuries caused by distraction spinal cord injury and clarify the effects of different degrees and durations of distraction on the primary injuries associated with spinal cord injury.We provide new concepts for the establishment of a model of distraction spinal cord injury and related basic research,and provide reference guidelines for the clinical diagnosis and treatment of this disease.