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.

Building Feedback-Regulation System Through Atomic Design for Highly Active SO_(2)Sensing

Reasonably constructing an atomic interface is pronouncedly essential for surface-related gas-sensing reaction.Herein,we present an ingen-ious feedback-regulation system by changing the interactional mode between single Pt atoms and adjacent S species for high-efficiency SO_(2)sensing.We found that the single Pt sites on the MoS_(2)surface can induce easier volatiliza-tion of adjacent S species to activate the whole inert S plane.Reversely,the activated S species can provide a feedback role in tailoring the antibonding-orbital electronic occupancy state of Pt atoms,thus creating a combined system involving S vacancy-assisted single Pt sites(Pt-Vs)to synergistically improve the adsorption ability of SO_(2)gas molecules.Further-more,in situ Raman,ex situ X-ray photoelectron spectroscopy testing and density functional theory analysis demonstrate the intact feedback-regulation system can expand the electron transfer path from single Pt sites to whole Pt-MoS_(2)supports in SO_(2)gas atmosphere.Equipped with wireless-sensing modules,the final Pt1-MoS_(2)-def sensors array can further realize real-time monitoring of SO_(2)levels and cloud-data storage for plant growth.Such a fundamental understanding of the intrinsic link between atomic interface and sensing mechanism is thus expected to broaden the rational design of highly effective gas sensors.

Ultrasonic enhancement of persulfate oxidation system governs emerging pollutants decontamination

Emerging contaminants (ECs) are widely present in aquatic environments, posing potential risks to both ecosystems and human health. Theultrasound-assisted persulfate oxidation process has attracted considerable attention in the degradation of ECs due to its ability to generate bothsulfate radicals and cavitation effects, enhancing degradation effects. In this paper, the principle of ultrasonic synergistic Fenton-like oxidationsystem for degrading organic pollutants was reviewed, divided into homogeneous system, non-homogeneous system, and single-atom system toexplore the synergistic effect of ultrasound-enhanced persulfate technology in three aspects, and the effects of environmental factors such asultrasonic frequency and power, system pH, temperature, and initial oxidant concentration on the system's decontamination performance werediscussed. Finally, future research on ultrasonically activated persulfate technology is summarized and prospected.

Research on modeling and self-excited vibration mechanism in magnetic levitation-collision interface coupling system

The modeling and self-excited vibration mechanism in the magnetic levitation-collision interface coupling system are investigated.The effects of the control and interface parameters on the system's stability are analyzed.The frequency range of self-excited vibrations is investigated from the energy point of view.The phenomenon of self-excited vibrations is elaborated with the phase trajectory.The corresponding control strategies are briefly analyzed with respect to the vibration mechanism.The results show that when the levitation objects collide with the mechanical interface,the system's vibration frequency becomes larger with the decrease in the collision gap;when the vibration frequency exceeds the critical frequency,the electromagnetic system continues to provide energy to the system,and the collision interface continuously dissipates energy so that the system enters the self-excited vibration state.

Synthesis and Coloring Mechanism of Metallic Glaze in R_(2)O-RO-Al_(2)O_(3)-SiO_(2)-P_(2)O_(5)System

A copper-red and silver-white metallic glaze of R_(2)O-RO-Al_(2)O_(3)-SiO_(2)-P_(2)O_(5)system was synthesized by adjusting the firing temperature and glaze components.The coloration mechanism of the metallic glaze was revealed via investigation of the microstructure of the glaze.Our research reveals that the metallic glaze with different colors is mainly due to the amount of Fe_(2)O_(3).The metallic glaze shows a silver-white luster due to a structural color ofα-Fe_(2)O_(3)crystals with a good orientation when the sample contains 0.0939 mol of Fe_(2)O_(3),maintaining temperatures at 1150℃for 0.5 h.The metallic glaze is copper-red which is dominated by the coupling of chemical and structural color ofα-Fe_(2)O_(3)crystals when the sample contains 0.0783 mol of Fe_(2)O_(3).After testing the amount of SiO_(2),we find that 4.0499 mol is the optimal amount to form the ceramic network,and 0.27 mol AlPO_(4)is the best amount to promote phase separation.

The Middle Miocene lobe-shaped and band-shaped submarine fans in the Lingshui Sag,Qiongdongnan Basin:source-to-sink system,genesis and implication

Deepwater oil and gas exploration is the key to sustainable breakthroughs in petroleum exploration worldwide.The Central Canyon gas field has confirmed the Lingshui Sag is a hydrocarbon-generating sag,and the deepwater reservoirs in the Lingshui Sag still have more fabulous oil and gas exploration potential.Based on drilling data and three-dimensional(3D)seismic data,this paper uses seismic facies analysis,seismic attribute analysis,and coherence slice analysis to identify the types of submarine fans(lobe-shaped and band-shaped submarine fans)that developed in the Lingshui Sag during the Middle Miocene,clarify the source-to-sink system of the submarine fans and discuss the genesis mechanism of the submarine fans.The results show that:(1)the deepwater source-to-sink system of the Lingshui Sag in the Middle Miocene mainly consisted of a“delta(sediment supply)-submarine canyon(sediment transport channel)-submarine fan(deepwater sediment sink)”association;(2)the main factor controlling the formation of the submarine fans developed in the Lingshui Sag was on the relative sea level decline;and(3)the bottom current reworked the lobe-shaped submarine fan that developed in the northern Lingshui Sag and formed the band-shaped submarine fan with a greater sand thickness.This paper aims to provide practical geological knowledge for subsequent petroleum exploration and development in the deepwater area of the Qiongdongnan Basin through a detailed analysis of the Middle Miocene submarine fan sedimentary system developed in the Lingshui Sag.

Reinforcement learning based adaptive control for uncertain mechanical systems with asymptotic tracking

This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.

Mechanism of selective laser trabeculoplasty:a systemic review

Although selective laser trabeculoplasty(SLT)is a recognized method for the treatment of glaucoma,the exact changes in the target tissue and mechanism for its intraocular pressure lowing effect are still unclear.The purpose of this review is to summarize the potential mechanisms of SLT on trabecular meshwork both in vivo and in vitro,so as to reveal the potential mechanism of SLT.SLT may induce immune or inflammatory response in trabecular meshwork(TM)induced by possible oxidative damage etc,and remodel extracellular matrix.It may also induce monocytes to aggregate in TM tissue,increase Schlemm’s canal(SC)cell conductivity,disintegrate cell junction and promote permeability through autocrine and paracrine forms.This provides a theoretical basis for SLT treatment in glaucoma.

Effect of Lightweight Aggregates Incorporation on the Mechanical Properties and Shrinkage Compensation of a Cement-Ground Granulated Blast Furnace Slag-Phosphogypsum Ternary System

Shrinkage-induced cracking is a common issue in concrete structures,where the formation of cracks not only affects the aesthetic appearance of concrete but also potentially reduces its durability and strength.In this study,the effect of ceramsite sand addition on the properties of a ternary system of cement-ground granulated blast furnace slag(GGBFS)-phosphogypsum(PG)is investigated.In particular,the fluidity,rheology,hydration heat,compressive strength,autogenous shrinkage,and drying shrinkage of the considered mortar specimens are analyzed.The results indicate that an increase in PG content leads to a decrease in fluidity,higher viscosity,lower exothermic peak,and lower compressive strength.However,the shrinkage of the mortar specimens is effectively compensated.The incorporation of internal curing water from ceramsite sand improves fluidity,decreases both yield stress and viscosity,enhances the degree of hydration,and induces mortar expansion.However,the inferior mechanical properties of the ceramsite sand generally produce a decrease in the compressive strength.

A novel mitigation measure for normal fault-induced deformations on pile-raft systems

Evidence from recent earthquakes has shown destructive consequences of fault-induced permanent ground movement on structures.Such observations have increased the demand for improvements in the design of structures that are dramatically vulnerable to surface fault ruptures.In this study a novel connection between the raft and the piles is proposed to mitigate the hazards associated with a normal fault on pile-raft systems by means of 3D finite element(FE)modeling.Before embarking on the parametric study,the strain-softening constitutive law used for numerical modeling of the sand has been validated against centrifuge test results.The exact location of the fix-head and unconnected pile-raft systems relative to the outcropping fault rupture in the free-field is parametrically investigated,revealing different failure mechanisms.The performance of the proposed connection for protecting the pile-raft system against normal fault-induced deformations is assessed by comparing the geotechnical and structural responses of both types of foundation.The results indicate that the pocket connection can relatively reduce the cap rotation and horizontal and vertical displacements of the raft in most scenarios.The proposed connection decreases the bending moment response of the piles to their bending moment capacity,verging on a fault offset of 0.6 m at bedrock.

Adaptive battery thermal management systems in unsteady thermal application contexts

With the increasing attention paid to battery technology,the microscopic reaction mechanism and macroscopic heat transfer process of lithium-ion batteries have been further studied and understood from both academic and industrial perspectives.Temperature,as one of the key parameters in the physical fra mework of batteries,affects the performa nce of the multi-physical fields within the battery,a nd its effective control is crucial.Since the heat generation in the battery is determined by the real-time operating conditions,the battery temperature is essentially controlled by the real-time heat dissipation conditions provided by the battery thermal management system.Conventional battery thermal management systems have basic temperature control capabilities for most conventional application scenarios.However,with the current development of la rge-scale,integrated,and intelligent battery technology,the adva ncement of battery thermal management technology will pay more attention to the effective control of battery temperature under sophisticated situations,such as high power and widely varied operating conditions.In this context,this paper presents the latest advances and representative research related to battery thermal management system.Firstly,starting from battery thermal profile,the mechanism of battery heat generation is discussed in detail.Secondly,the static characteristics of the traditional battery thermal management system are summarized.Then,considering the dynamic requirements of battery heat dissipation under complex operating conditions,the concept of adaptive battery thermal management system is proposed based on specific research cases.Finally,the main challenges for battery thermal management system in practice are identified,and potential future developments to overcome these challenges are presented and discussed.

Local Torrential Rainfall Event within a Mei-Yu Season Mesoscale Convective System:Importance of Back-Building Processes

An extreme rainfall event occurred over Hangzhou,China,during the afternoon hours on 24 June 2013.This event occurred under suitable synoptic conditions and the maximum 4-h cumulative rainfall amount was over 150 mm.This rainfall event had two major rainbands.One was caused by a quasi-stationary convective line,and the other by a backbuilding convective line related to the interaction of the outflow boundary from the first rainband and an existing low-level mesoscale convergence line associated with a mei-yu frontal system.The rainfall event lasted 4 h,while the back-building process occurred in 2 h when the extreme rainfall center formed.So far,few studies have examined the back-building processes in the mei-yu season that are caused by the interaction of a mesoscale convergence line and a convective cold pool.The two rainbands are successfully reproduced by the Weather Research and Forecasting(WRF)model with fourlevel,two-way interactive nesting.In the model,new cells repeatedly occur at the west side of older cells,and the backbuilding process occurs in an environment with large CAPE,a low LFC,and plenty of water vapor.Outflows from older cells enhance the low-level convergence that forces new cells.High precipitation efficiency of the back-building training cells leads to accumulated precipitation of over 150 mm.Sensitivity experiments without evaporation of rainwater show that the convective cold pool plays an important role in the organization of the back-building process in the current extreme precipitation case.

Recommendation System Based on Perceptron and Graph Convolution Network

The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution network.The current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction data.This paper presents a new approach to address such issues,utilizing the graph convolution network to extract association relations.The proposed approach mainly includes three modules:Embedding layer,forward propagation layer,and score prediction layer.The embedding layer models users and items according to their interaction information and generates initial feature vectors as input for the forward propagation layer.The forward propagation layer designs two parallel graph convolution networks with self-connections,which extract higher-order association relevance from users and items separately by multi-layer graph convolution.Furthermore,the forward propagation layer integrates the attention factor to assign different weights among the hop neighbors of the graph convolution network fusion,capturing more comprehensive association relevance between users and items as input for the score prediction layer.The score prediction layer introduces MLP(multi-layer perceptron)to conduct non-linear feature interaction between users and items,respectively.Finally,the prediction score of users to items is obtained.The recall rate and normalized discounted cumulative gain were used as evaluation indexes.The proposed approach effectively integrates higher-order information in user entries,and experimental analysis demonstrates its superiority over the existing algorithms.

An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based estimation.Since the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed.First,an image fingerprint construction is proposed for training data.After the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline interpolation.Then,the linear mapping and the gray-color transformation method are proposed to form the color image fingerprint.Second,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance improvement.At last,an experiment is carried out to evaluate the estimation performance.Compared with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.

Exploring the impacts of major events on the systemic risk of the international energy market

This study examines the systemic risk caused by major events in the international energy market(IEM)and proposes a management strategy to mitigate it. Using the tail-event driven network(TENET)method, this study constructed a tail-risk spillover network(TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets(SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

Characteristics and genetic mechanism of the Mesoproterozoic rift system,Ordos Basin,China

The Mesoproterozoic rifts are developed in the Ordos Basin located in the western margin of the North China Plate.Based on the latest 3D seismic data and previous research results,this study intends to discuss the zonal differential deformation characteristics and genetic mechanism of the Mesoproterozoic rifts in the Ordos Basin.NE-trending rifts are developed in the Mesoproterozoic in the south-central Ordos Basin,the main part of which are located near the western margin of the North China Plate.NNW-trending rifts are developed in the north of the basin,while NW-NNW rifts in the Mesoproterozoic in Hangjinqi area.The genetic mechanism of the Mesoproterozoic rifts is related to regional extensional stress field,plate boundary conditions and internal preexisting structures.The main extensional stress direction strikes NWW-SSE(120°)in the western margin of the North China Plate,based on the forward rift trend of the northern Mesoproterozoic.In Hangjinqi area,the reactivation of the existing NWtrending Wulansu fault and NW-NW-trending Daolao fault,results in dextral shear stress field.The boundary between the western margin of the North China Plate and its adjacent plates forms a nearly NS-trending preexisting basement tectonic belt,which intersects with the NWW-SSE(120°)extensional stress at an acute angle of 60°.Therefore,the western margin of the North China Plate is formed by oblique normal faults under oblique extension.Due to the long time span of Columbia Supercontinent breakup(1.8e1.6 Ga),the oblique rift in the south-central Ordos Basin is formed under the continuous oblique extension at the western margin of the North China Plate.

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.

Prediction and Output Estimation of Pattern Moving in Non-Newtonian Mechanical Systems Based on Probability Density Evolution

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

A Nonlinear Explicit Model of A Non-Circular Subsea Tunnel-Liner System with An FGM Inverted Arch Under Mechanical Loading and Fire Fields

This paper proposes an explicit scheme to analyze the failure of a subsea polyhedral tunnel-liner system with an inverted arch under mechanical loading and fire fields.The thin-walled liner is made of Functionally Graded Materials(FGMs),which may improve the stability behavior of the tunnel-liner system.Hydrostatic pressure is inevitable in the liner since underground water may penetrate the cracks of the tunnel,and reach the outer surface of the liner.In addition,an elevated temperature loading is taken into account,considering that fire may occur in the tunnel-liner system.Under the combination of mechanical loading and thermal loading,the liner deforms into a single-lobe shape,which is depicted by a trigonometric function.The total potential energy is expressed quantitatively after the energy approach and thin-walled shell theory are used.The minimum potential energy is obtained when the critical buckling occurs.The critical buckling pressure is calculated,which considers the effect of the thermal field.The present analytical prediction is subsequently compared precisely with other closed-form solutions.Finally,the effects of several parameters,such as the geometric shapes,temperature variations,and volume fraction indices,are discussed to further survey the buckling performance of the nonlinear buckling of an FGM polyhedral liner with an inverted arch.One may address a polyhedral liner with fewer polyhedral sides,and a lower volume fraction index is recommended to rehabilitate cracked tunnels in engineering applications.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.