Development and study on automatic balancer based on counter weight by magnetic force

Rotating machines are very sensitive to mass unbalance which has a harmful effect on its running accuracy and service life. Therefore,a variety of dynamic balancing methods and devices are studied to reduce the vibration caused by mass unbalance. On-line active balancing is a new balancing procedure which is more convenient and precise than the previous methods. In this paper,an electromagnetic balancer based on ring coils and permanent magnets is presented. The balancer has a simple structure and the self-locking function without clutch,and transfers power by the non-contact electromagnetic field. In order to justify the rationality of its design,a two-dimension(2D) electromagnetic finite element model is conducted to verify that this magnetic circuit has no flux leakage and saturation. A three-dimension (3D) 1/10 model of the balancer is built to obtain the self-locking torque and driving torque. Based on the research work above,an electromagnetic balancer is developed. By testing the balancer using COCO80,it is verified effective to reduce the rotor unbalance at the speed of 1300 r/min.

P-ACOHONEYBEE: A Novel Load Balancer for Cloud Computing Using Mathematical Approach

Cloud computing is a collection of disparate resources or services,a web of massive infrastructures,which is aimed at achieving maximum utilization with higher availability at a minimized cost.One of the most attractive applications for cloud computing is the concept of distributed information processing.Security,privacy,energy saving,reliability and load balancing are the major challenges facing cloud computing and most information technology innovations.Load balancing is the process of redistributing workload among all nodes in a network;to improve resource utilization and job response time,while avoiding overloading some nodes when other nodes are underloaded or idle is a major challenge.Thus,this research aims to design a novel load balancing systems in a cloud computing environment.The research is based on the modification of the existing approaches,namely;particle swarm optimization(PSO),honeybee,and ant colony optimization(ACO)with mathematical expression to form a novel approach called PACOHONEYBEE.The experiments were conducted on response time and throughput.The results of the response time of honeybee,PSO,SASOS,round-robin,PSO-ACO,and P-ACOHONEYBEE are:2791,2780,2784,2767,2727,and 2599(ms)respectively.The outcome of throughput of honeybee,PSO,SASOS,round-robin,PSO-ACO,and P-ACOHONEYBEE are:7451,7425,7398,7357,7387 and 7482(bps)respectively.It is observed that P-ACOHONEYBEE approach produces the lowest response time,high throughput and overall improved performance for the 10 nodes.The research has helped in managing the imbalance drawback by maximizing throughput,and reducing response time with scalability and reliability.

Conception and Design of Active Balancer for Planar Mechanisms

The dynamic balancing is an important issue in mechanism design. For the existing balancing methods, both passive and active ones, there is still room for improvement in adaplability and independency. In view of this, a concept of active balancer is developed as a new solution for the dynamic balancing with more flexibility. The proposed balancer is an independent additional device with a control system inside, which consists of a two-degree-of-freedom （DOF） linkage and a controllable motor, and can be attached to a machine expediently with little change to its original structure and motion. One of the two inputs of the two-DOF linkage shares the same shaft with its output, which is connected to the input shaft of a machine to be balanced and driven by the original actuator. The other input is driven by the control motor. By properly selecting the speed trajectories of the control motor and link parameters of the two-DOF linkage, one or more dynamic effects of the mechanisms can be minimized or eliminated adaptively. The design procedure of the active balancer is put forward and a two-step optimization is developed to find out optimal design parameters of the balancer for various design requirements and constraints. Taking a force-balanced crank-rocker mechanism as the reference mechanism, numerical examples are given to illustrate the design procedure. The balancing effects of the proposed balancer are compared with those of the existing adding dyads （DYAD） method. The results show that the introduction of the control system provides the active balancer with better balancing effect and more flexibility than the DYAD method. A considerable reduction in the dynamic effects （input torque, shaking moment and shaking force） can be achieved for different balancing object by designing the structural and control parameters of the balancer, and the deterioration of dynamic performance caused by alterative working conditions can be compensated effectively by redesigning the control parameters.

Systematic Review:Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms

Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led to a significant increase in the user demand for services.However,in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization.This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms.Specifically,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic.In a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing techniques.It also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS parameters.Additionally,the analysis evaluates the tools and instruments utilized in each investigated study.Moreover,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the CloudSim simulation tool is also performed.Finally,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.

Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

Na^(+)/K^(+)-ATPase:ion pump,signal transducer,or cytoprotective protein,and novel biological functions

Na^(+)/K^(+)-ATPase is a transmembrane protein that has important roles in the maintenance of electrochemical gradients across cell membranes by transporting three Na^(+)out of and two K^(+)into cells.Additionally,Na^(+)/K^(+)-ATPase participates in Ca^(2+)-signaling transduction and neurotransmitter release by coordinating the ion concentration gradient across the cell membrane.Na^(+)/K^(+)-ATPase works synergistically with multiple ion channels in the cell membrane to form a dynamic network of ion homeostatic regulation and affects cellular communication by regulating chemical signals and the ion balance among different types of cells.Therefo re,it is not surprising that Na^(+)/K^(+)-ATPase dysfunction has emerged as a risk factor for a variety of neurological diseases.However,published studies have so far only elucidated the important roles of Na^(+)/K^(+)-ATPase dysfunction in disease development,and we are lacking detailed mechanisms to clarify how Na^(+)/K^(+)-ATPase affects cell function.Our recent studies revealed that membrane loss of Na^(+)/K^(+)-ATPase is a key mechanism in many neurological disorders,particularly stroke and Parkinson's disease.Stabilization of plasma membrane Na^(+)/K^(+)-ATPase with an antibody is a novel strategy to treat these diseases.For this reason,Na^(+)/K^(+)-ATPase acts not only as a simple ion pump but also as a sensor/regulator or cytoprotective protein,participating in signal transduction such as neuronal autophagy and apoptosis,and glial cell migration.Thus,the present review attempts to summarize the novel biological functions of Na^(+)/K^(+)-ATPase and Na^(+)/K^(+)-ATPase-related pathogenesis.The potential for novel strategies to treat Na^(+)/K^(+)-ATPase-related brain diseases will also be discussed.

Attribution of Biases of Interhemispheric Temperature Contrast in CMIP6 Models

One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.

Nanopriming with selenium doped carbon dots improved rapeseed germination and seedling salt tolerance

Soil salinity is a big environmental issue affecting crop production.Although seed nanopriming has been widely used to improve seed germination and seedling growth under salinity,our knowledge about the underlying mechanisms is still insufficient.Herein,we newly synthesized selenium-doped carbon dots nanoparticles coated with poly acrylic acid(poly acrylic acid coated selenium doped carbon dots,PAA@Se-CDs)and used it to prime seeds of rapeseeds.The TEM(transmission electron microscope)size and zeta potential of PAA@Se-CDs are 3.8±0.2 nm and-30 mV,respectively.After 8 h priming,the PAA@Se-CDs nanoparticles were detected in the seed compartments(seed coat,cotyledon,and radicle),while no such signals were detected in the NNP(no nanoparticle control)group(SeO_2 was used as the NNP).Nanopriming with PAA@Se-CDs nanoparticles increased rapeseeds germination(20%)and seedling fresh weight(161%)under saline conditions compared to NNP control.PAA@Se-CDs nanopriming significantly enhanced endo-β-mannanase activities(255%increase,21.55μmol h^(-1)g^(-1)vs.6.06μmol h^(-1)g^(-1),at DAS 1(DAS,days after sowing)),total soluble sugar(33.63 mg g^(-1)FW(fresh weight)vs.20.23 mg g^(-1)FW)and protein contents(1.96μg g^(-1)FW vs.1.0μg g^(-1)FW)to support the growth of germinating seedlings of rapeseeds under salt stress,in comparison with NNP co ntrol.The respiration rate and ATP content were increased by 76%and 607%,respectively.The oxidative damage of salinity due to the overaccumulation of reactive oxygen species(ROS)was alleviated by PAA@Se-CDs nanopriming by increasing the antioxidant enzyme activities(SOD(superoxide dismutase),POD(peroxidase),and CAT(catalase)).Another mechanism behind PAA@Se-CDs nanopriming improving rapeseeds salt tolerance at seedling stage was reducing sodium(Na^(+))accumulation and improving potassium(K^(+))retention,hence increasing the K^(+)/Na^(+)ratio under saline conditions.Overall,our results not only showed that seed nanopriming with PAA@Se-CDs could be a good approach to improve salt tolerance,but also add more knowledge to the mechanism behind nanopriming-improved plant salt tolerance at germination and early seedling growth stage.

Soleus arthrogenic muscle inhibition following acute lateral ankle sprain correlates with symptoms and ankle disability but not with postural control

Background:Acute lateral ankle sprains(ALAS)are associated with long-term impairments and instability tied to altered neural excitability.Arthrogenic muscle inhibition(AMI)has been observed in this population;however,relationships with injury-related impairments are unclear,potentially due to the resting,prone position in which AMI is typically measured.Assessing AMI during bipedal stance may provide a better understanding of this relationship.Methods:AMI was assessed in 38 young adults(19 ALAS within 72 h of injury:10 males,21.4±2.7 years;19 healthy controls:10 males,21.9±2.2 years;mean±SD)using the Hoffmann reflex(H-reflex)during bipedal stance.Electrical stimulation was administered to identify the _(max)imal H-reflex(H_(max))and _(max)imal motor response(M_(max))from the soleus,fibularis longus,and tibialis anterior muscles.The primary outcome measure was the H_(max)/M_(max) ratio.Secondary outcomes included acute symptoms(pain and swelling),postural control during bipedal stance,and self-reported function.Results:No significant group-by-limb interactions were observed for any muscle.However,a significant group main effect was observed in the soleus muscle(F(1,35)=6.82,p=0.013),indicating significantly lower H_(max)/M_(max) ratios following ALAS(0.38±0.20)compared to healthy controls(0.53±0.16).Furthermore,lower H_(max)/M_(max) ratios in the soleus significantly correlated with acute symptoms and self-reported function but not with postural control.Conclusion:This study supports previous evidence of AMI in patients with ALAS,providing insight into neurophysiologic impacts of musculoskeletal injury.Our results suggest that assessing AMI in a standing position following acute injury may provide valuable insight into how AMI develops and guide potential therapeutic options to curb and offset the formation of joint instability.

Theoretical study of particle and energy balance equations in locally bounded plasmas

In this study,new particle and energy balance equations have been developed to predict the electron temperature and density in locally bounded plasmas.Classical particle and energy balance equations assume that all plasma within a reactor is completely confined only by the reactor walls.However,in industrial plasma reactors for semiconductor manufacturing,the plasma is partially confined by internal reactor structures.We predict the effect of the open boundary area(A′_(L,eff))and ion escape velocity(u_(i))on electron temperature and density by developing new particle and energy balance equations.Theoretically,we found a low ion escape velocity(u_(i)/u_(B)≈0.2)and high open boundary area(A′_(L,eff)/A_(T,eff)≈0.6)to result in an approximately 38%increase in electron density and an 8%decrease in electron temperature compared to values in a fully bounded reactor.Additionally,we suggest that the velocity of ions passing through the open boundary should exceedω_(pi)λ_(De)under the condition E^(2)_(0)?(Φ/λ_(De))^(2).

Hydrodynamic and trophic variations reshape macroinvertebrate food webs in urban ecosystems

Urbanization is modifying aquatic ecosystems,with hydrodynamic and trophic variations altering biotic assemblages in rapidly expanding cities worldwide.Despite the fundamental bioenergetic role of food webs within these assemblages,their responding mechanism to the hydrodynamic and trophic variations remains largely unknown.Here we show that hydrodynamic and trophic loss,coupled with the weakening of cascade controls by key trophic guilds,leads to a significant decline in the structure,function and stability of macroinvertebrate food webs.Utilizing the allometric diet breadth model and biomass balance model,we established representative food webs for macroinvertebrate groups under varying hydrodynamic and trophic stresses.We found that such losses have reduced∼75%trophic guild richness,∼85%biomass flux,and∼80%biomass storage.These reductions promote trophic guild specialization,further destabilizing food web,eroding interactive strength asymmetry,and diminishing the control of trophic guilds.Furthermore,macroinvertebrate food webs show divergent stability responses under similar stress levels,mainly driven by differences in the cascade controls exerted by key trophic guilds.Our results underscore the critical role of hydrodynamic and trophic variations in shaping urban aquatic ecosystems and highlight the significance of both external environmental revitalization and internal food web dynamics enhancement in restoring the ecological stability in urban settings.

CFD-PBM coupled modeling of the liquid-liquid dispersion characteristics and structure optimization for Kenics static mixer

Kenics static mixers(KSM)are extensively used in industrial mixing-reaction processes by virtue of high mixing efficiency,low power homogenization and easy continuous production.Resolving liquid droplet size and its distribution and thus revealing the dispersion characteristics are of great significance for structural optimization and process intensification in the KSM.In this work,a computational fluid dynamics-population balance model(CFD-PBM)coupled method is employed to systematically investigate the effects of operating conditions and structural parameters of KSM on droplet size and its distribution,to further reveal the liquid-liquid dispersion characteristics.Results indicate that higher Reynolds numbers or higher dispersed phase volume fractions increase energy dissipation,reducing Sauter mean diameter(SMD)of dispersed phase droplets and with a shift in droplet size distribution(DSD)towards smaller size.Smaller aspect ratios,greater blade twist and assembly angles amplify shear rate,leading to smaller droplet size and a narrower DSD in the smaller range.The degree of impact exerted by the aspect ratio is notably greater.Notably,mixing elements with different spin enhance shear and stretching efficiency.Compared to the same spin,SMD becomes 3.7-5.8 times smaller in the smaller size range with a significantly narrower distribution.Taking into account the pressure drop and efficiency in a comprehensive manner,optimized structural parameters for the mixing element encompass an aspect ratio of 1-1.5,a blade twist angle of 180°,an assembly angle of 90°,and interlaced assembly of adjacent elements with different spin.This work provides vital theoretical underpinning and future reference for enhancing KSM performance.

Unveiling evapotranspiration patterns and energy balance in a subalpine forest of the Qinghai-Tibet Plateau:observations and analysis from an eddy covariance system

Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qinghai-Tibet Plateau,an open-path eddy covariance system was set up to monitor the forest from November 2020 to October 2021 in a core area of the Three Parallel Rivers in the Qing-hai-Tibet Plateau.The results show that the evapotranspira-tion peaked daily,the maximum occurring between 11:00 and 15:00.Environmental factors had significant effects on evapotranspiration,among them,net radiation the greatest(R^(2)=0.487),and relative humidity the least(R^(2)=0.001).The energy flux varied considerably in different seasons and sensible heat flux accounted for the main part of turbulent energy.The energy balance ratio in the dormant season was less than that in the growing season,and there is an energy imbalance at the site on an annual time scale.

Distributed Graph Database Load Balancing Method Based on Deep Reinforcement Learning

This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies.Unlike indepen-dent batch tasks,workflows typically consist of multiple subtasks with intrinsic correlations and dependencies.It necessitates the distribution of various computational tasks to appropriate computing node resources in accor-dance with task dependencies to ensure the smooth completion of the entire workflow.Workflow scheduling must consider an array of factors,including task dependencies,availability of computational resources,and the schedulability of tasks.Therefore,this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based on deep reinforcement learning(DRL).The method optimizes the maximum completion time(makespan)and response time of workflow tasks,aiming to enhance the responsiveness of workflow tasks while ensuring the minimization of the makespan.The experimental results indicate that the Q-learning Deep Reinforcement Learning(Q-DRL)algorithm markedly diminishes the makespan and refines the average response time within distributed graph database environments.In quantifying makespan,Q-DRL achieves mean reductions of 12.4%and 11.9%over established First-fit and Random scheduling strategies,respectively.Additionally,Q-DRL surpasses the performance of both DRL-Cloud and Improved Deep Q-learning Network(IDQN)algorithms,with improvements standing at 4.4%and 2.6%,respectively.With reference to average response time,the Q-DRL approach exhibits a significantly enhanced performance in the scheduling of workflow tasks,decreasing the average by 2.27%and 4.71%when compared to IDQN and DRL-Cloud,respectively.The Q-DRL algorithm also demonstrates a notable increase in the efficiency of system resource utilization,reducing the average idle rate by 5.02%and 9.30%in comparison to IDQN and DRL-Cloud,respectively.These findings support the assertion that Q-DRL not only upholds a lower average idle rate but also effectively curtails the average response time,thereby substantially improving processing efficiency and optimizing resource utilization within distributed graph database systems.

Transverse momentum balance of dijets in Xe+Xe collisions at the LHC

We present a theoretical study of the medium modifications of the p_(T)balance (x_(J)) of dijets in Xe+Xe collisions at■.The initial production of dijets was carried out using the POWHEG+PYTHIA8 prescription,which matches the next-toleading-order (NLO) QCD matrix elements with the parton shower (PS) effect.The SHELL model described the in-medium evolution of nucleus–nucleus collisions using a transport approach.The theoretical results of the dijet xJin the Xe+Xe collisions exhibit more imbalanced distributions than those in the p+p collisions,consistent with recently reported ATLAS data.By utilizing the Interleaved Flavor Neutralisation,an infrared-and-collinear-safe jet flavor algorithm,to identify the flavor of the reconstructed jets,we classify dijets processes into three categories:gluon–gluon (gg),quark–gluon (qg),and quark–quark (qq),and investigated the respective medium modification patterns and fraction changes of the gg,qg,and qq components of the dijet sample in Xe+Xe collisions.It is shown that the increased fraction of qg component at a small x_(J)contributes to the imbalance of the dijet;in particular,the q_(1)g_(2)(quark-jet-leading) dijets experience more significant asymmetric energy loss than the g_(1)q_(2)(gluon-jet-leading) dijets traversing the QGP.By comparing the■of inclusive,■ dijets in Xe+Xe collisions,we observe■.Moreover,ρ_(Xe),P_(b),the ratios of the nuclear modification factors of dijets in Xe+Xe to those in Pb+Pb,were calculated,which indicates that the yield suppression of dijets in Pb+Pb is more pronounced than that in Xe+Xe owing to the larger radius of the lead nucleus.

Joint position optimization,user association,and resource allocation for load balancing in UAV-assisted wireless networks

Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell.To fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent cells.To tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV position.Then,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation schemes.We further propose an iterative power allocation algorithm based on the sequential convex approximation theory.The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.

Regulating metal-acid double site balance on mesoporous SiO_(2)-Al_(2)O_(3) composite oxide for supercritical n-decane cracking

The balance between metal and acid sites directly affects the preparation of high-performance cracking catalysts with high heat sink and low coking.Nevertheless,how to control acid-metal sites balance and its relationship with cracking performance are reported scarcely.In this work,a series of Pt/Al_(2)O_(3)-SiO_(2) dual sites catalysts with different metal to acid active sites ratio(C_(M)/C_(SA))were constructed by ethanolassisted impregnation method and the impact on n-decane cracking under supercritical conditions was systematically and deeply investigated.The results showed that the conversion and carbon deposition increased gradually with varied C_(M)/C_(SA)and reached the balance at C_(M)/C_(SA)of 0.13.The proper ratio C_(M)/C_(SA)(0.13)can balance the deep dehydrogenation coking over metal active sites and high heat sink of cracking over acid active sites,the chemical heat sink reaches amazing 1.75 MJ/kg and carbon deposition is only22.03 mg/cm^(2) at 750℃.Meanwhile,the few metal sites at low C_(M)/C_(SA)and the few strong acid sites at high C_(M)/C_(SA)are the main factors limiting the cracking activity.Low C_(M)/C_(SA)limit the activation of C-H bond and deep dehydrogenation of coking precursor,resulting in relative low cracking activity and carbon deposition,while high C_(M)/C_(SA)limit the activation of C-C bond and increase the deep dehydrogenation.In this contribution,design and construction of metal-acid dual sites can not only provide the technical solution for the preparation of high heat sink and low coking cracking catalyst,but also deepen the understanding of the cracking path of hydrocarbon fuel.

Coupling Coordination Analysis of Cropland Intensification and Agroecosystem Services:Evidence from Loess Plateau in Shaanxi Province,China

One of the greatest challenges in the agroecosystem is to improve cropland intensification while preserving agroecosystem services.While many studies have investigated the effect of cropland intensification on agroecosystem service,the interactive coupling and coordination among these factors remain largely unexplored.In view of this,this study performed a case study of the Loess Plateau in Shaanxi Province,China and constructed comprehensive evaluation models to quantify the cropland intensification and agroecosystem service in this area.Balance analysis and the coupling coordination degree model were used to evaluate the interactive relationship between cropland intensification and agroecosystem service,and statistical analysis and spatial autocorrelation were used to analyze the spatial characteristics and potential mechanism of the coupling coordination.Results show that both the cropland intensification and agroecosystem service in the study area were relatively low yet gradually increased from 2000 to 2020.Agroecosystem service lag was identified as the dominant unbalanced development type.Improving the supply capacity of agroecosystem services plays a key role in the balanced development of cropland in the Loess Plateau.The coupling coordination degree between cropland intensification and agroecosystem service ranges from basic coordination to serious incoordination.Therefore,cropland intensification practices in the area should be optimized to enhance this coordination degree.An upward trend was also observed in the coupling coordination degree from2000 to 2020.The withdrawal of marginal cropland in the Grain for Green program is one of the most important reasons for this trend,especially for the northern region.Around 83.6%of the high-high clusters are concentrated in the southern region of the Loess Plateau,whereas 70.5%of the low-low clusters are distributed in the northern region.These clustering characteristics are mainly attributed to the environmental suitability of these areas for agriculture and their degree of economic development.

Reduction of epinephrine in the lumbar spinal cord following repetitive blast-induced traumatic brain injury in rats

Traumatic brain inju ry-induced unfavorable outcomes in human patients have independently been associated with dysregulated levels of monoamines,especially epinephrine,although few preclinical studies have examined the epinephrine level in the central nervous system after traumatic brain injury.Epinephrine has been shown to regulate the activities of spinal motoneurons as well as increase the heart rate,blood pressure,and blood flow to the hindlimb muscles.Therefore,the purpose of the present study was to determine the impact of repeated blast-induced traumatic brain injury on the epinephrine levels in seve ral function-s pecific central nervous system regions in rats.Following three repeated blast injuries at 3-day intervals,the hippocampus,motor cortex,locus coeruleus,vestibular nuclei,and lumbar spinal cord were harvested at post-injury day eight and processed for epinephrine assays using a high-sensitive electrochemical detector cou pled with high-performance liquid chromatography.Our results showed that the epinephrine levels were significantly decreased in the lumbar spinal cord tissues of blast-induced traumatic brain injury animals compared to the levels detected in age-and sex-matched sham controls.In other function-specific central nervous system regions,although the epinephrine levels were slightly altered following blast-induced tra u matic brain injury,they were not statistically significant.These results suggest that blast injury-induced significant downregulation of epinephrine in the lumbar spinal cord could negatively impact the motor and cardiovascular function.This is the first repo rt to show altered epinephrine levels in the spinal cord following repetitive mild blast-induced traumatic brain injury.

Harmonic balance simulation of the influence of component uniformity and reliability on the performance of a Josephson traveling wave parametric amplifier

A Josephson traveling wave parametric amplifier(JTWPA),which is a quantum-limited amplifier with high gain and large bandwidth,is the core device of large-scale measurement and control systems for quantum computing.A typical JTWPA consists of thousands of Josephson junctions connected in series to form a transmission line and hundreds of shunt LC resonators periodically loaded along the line for phase matching.Because the variation of these capacitors and inductors can be detrimental to their high-frequency characteristics,the fabrication of a JTWPA typically necessitates precise processing equipment.To guide the fabrication process and further improve the design for manufacturability,it is necessary to understand how each electronic component affects the amplifier.In this paper,we use the harmonic balance method to conduct a comprehensive study on the impact of nonuniformity and fabrication yield of the electronic components on the performance of a JTWPA.The results provide insightful and scientific guidance for device design and fabrication processes.