“动机”理论在大学生思想政治教育中的应用

心理学研究表明,动机是人的一切心理活动中最重要的心理机能。在大学生思想政治教育中,应该认真分析大学生行为产生的心理动机因素,研究动机与行为产生之间的密切关系,并在思想政治教育中注意运用多种方式激发和培养大学生高尚的行为动机,以达到思想政治教育的目的和要求。由动机功能理论知,在大学生思想政治教育中激发高尚的动机,对于大学生形成积极的行为习惯具有重要作用。由动机性行为产生模式知,了解影响大学生行为表现的主客观因素是做好思想政治教育的前提。应用动机理论,通过提高目标引力、增强外界压力,改善外界调控以及加大内部动力,可以激励大学生产生积极行为,从而提高思想政治教育的实效性。

“动机簇”理论与鲁迅《伤逝》创作动机阐释难题——兼及《伤逝》研究中的“过度阐释”现象

学术界对《伤逝》创作动机(意图)的解读难以取得共识。运用建立在现代心理学理论基础上的“动机簇”理论解决这一阐释难题,是一种思路。第一,《伤逝》的创作是由“动机簇”完成的,“动机簇”是由多个创作动机形成的“丛簇”现象,因此《伤逝》的创作动机不是单一的,而具有多元并存的特征,其中至少包含一个“外部动机”和一个“内部动机”。第二,在《伤逝》的“动机簇”结构中,存在着主导动机与非主导动机、显明性创作动机和潜隐性创作动机的区别。第三,《伤逝》的创作动机虽然表现为多元化的“动机簇”现象,但并非没有限制的,创作动机数量的有限性决定了不能对《伤逝》的创作动机进行随意的、脱离作者或文本实际的“过度阐释”,而这种“过度阐释”现象在《伤逝》研究史上屡见不鲜,值得警惕。

“动机-机会-能力”(MOA)理论视角下重大工程承包商创新行为前因机制的探索性分析

重大工程已成为我国科技创新的重要平台,但由于创新过程复杂、投入大、风险高,以设计单位、施工单位为主的承包商作为核心主体在创新过程中积极性不高,造成工程领域技术进步缓慢、创新投入产出效率低,重大工程远未体现其创新驱动功能。为此,选取青藏铁路、港珠澳大桥、杨房沟水电站为案例,结合专家访谈对重大工程创新实践进行挖掘,基于“动机-机会-能力”(MOA)理论,从动机、能力、机会3个维度对承包商创新行为关键驱动因素进行分析提炼,构建重大工程承包方创新行为的前因机制模型。结果表明,制度压力和工程本身复杂性是承包方创新的直接驱动力,知识基础和吸收能力为其创新活动提供重要支撑,业主支持和创新网络结构则构成承包方创新行为的机会条件。因此,为有效激发重大工程中承包商创新行为,政府和业主方要遵循压力与动力并举的原则强化承包商创新动机,不断完善承包商创新能力的培养和提升,并加大对承包商创新行为的资源支持。

企业金融化抑制了低碳技术创新吗?——来自“动机背景”视角的观察与诠释

低碳化是实体企业的未来发展愿景,金融化是实体企业的现实发展特征,考察金融化对低碳技术创新的影响,对经济高质量发展和国家实业安全有重要的战略意义。该研究以2011—2021年中国沪深A股上市的制造业企业为样本,实证分析企业金融化对低碳技术创新的影响,探讨金融化“动机背景”在这一影响中的调节作用,并进一步分析了“动机背景”对低碳技术创新的非金融化影响机制。研究发现:①企业金融化程度的加深会抑制其低碳技术创新水平的提升,且这一抑制效果存在滞后性和黏性,在经过一系列稳健性和内生性检验后,该结论依然成立。②金融化对国有企业低碳技术创新投入和产出的抑制效果弱于非国有企业,对大规模企业的抑制效果弱于小规模企业,且在非国有企业和小规模企业中,金融化抑制低碳技术创新的滞后性和黏性效果更为突出。③基于“动机背景”角度的检验发现,盈利乐观度和行业竞争度的提升能够有效缓解企业金融化对低碳技术创新的抑制效果,而企业内部融资约束的增强则会加剧金融化对低碳技术创新的抑制作用。④“动机背景”对低碳技术创新的影响存在以管理者环境注意力转移为中介的非金融化影响渠道,盈利乐观度的提升能够转入管理者环境注意力,融资约束和行业竞争激烈程度会转出管理者的环境注意力,经过针对中介分析的内生性检验后,该结论依然成立。据此,该研究基于“动机背景”视角,从完善实体企业金融化监管、建立金融化风险防范体系、缓解企业融资压力、维护行业良性竞争秩序和企业管理者环境意识培育方面提出了增强企业低碳技术创新能力的措施及政策建议。

Effect of ultrasonic and mechanical vibration treatments on evolution of Mn-rich phases and mechanical properties of Al−12Si−4Cu−1Ni−1Mg−2Mn piston alloys

Effects of ultrasonic vibration(UV)and mechanical vibration(MV)on the Mn-rich phase modification and mechanical properties of Al−12Si−4Cu−1Ni−1Mg−2Mn piston alloys were investigated.The results show that the UV and UV+MV treatments can significantly refine and fragmentize the microstructures.In addition,UV treatment can significantly passivate the primary Mn-rich Al15Mn3Si2 intermetallics.The formation mechanisms of refinement and passivation of the grains and non-dendrite particles were discussed.Compared with the gravity die-cast alloys,the UV and UV+MV treated alloys exhibit improved tensile and creep resistance at room and elevated temperatures.These results can be attributed to the refinement of theα(Al)grains and the secondary intermetallics,the increased proportion of refined heat-resistant precipitates,and the formation of nano-sized Si particles.The ultimate tensile strength of the UV treated alloys at 350℃ exceeds that of commercial piston alloys.This indicates the high application potential of the developed piston alloys in density diesel engines.

Solution of idle LBO problem for high FAR aero combustor

The paper sheds light on the idle lean blow off(LBO)problem for high fuel air ratio(FAR)com⁃bustor,which is impossible to be addressed with traditional aero combustor design.A significant improvement in aero combustor design is required to resolve the idle LBO issue.The authors detailed a practical and efficient solu⁃tion,which not only solved the idle LBO issue but also defined the aero-thermal design for high-FAR combustor.The design will usher in a new era of aero combustor.

Simulation of Start-Up Process of Turbofan Engine Based on Full-State Characteristics of Fan

Difficulties in obtaining component characteristics in the sub-idle state of rotor constrain the simulation capabilities of ground and windmill start-up processes for turbofan engines.This paper proposes a backbone feature method based on conventional characteristics parameters to derive the full-state characteristics of fan.The application of the fan’s full-state characteristics in component-level model of turbofan engine enables zero-speed iterative simulation for ground start-up process and windmill simulation for windmill start-up process,thereby improving the simulation capability of sub-idle state during turbofan engine start-up.

有志者事成抑或有力者事成——省级数字政府专项政策采纳的影响因素和路径

数字政府专项政策旨在为数字政府发展把舵定向,厘清其扩散动因有利于协调政府数字化转型全局。既有研究疏于考察政策出台环节,多采用线性统计分析方法,在解释因果关系复杂的政策扩散时不无局限性。基于“动机—能力”视角,采用模糊集定性比较分析法探究省级数字政府专项政策采纳的影响因素及机制,可知,中央信号感知是数字政府专项政策较早采纳的必要条件,而公众需求、同侪竞争、社会舆论、数字治理能力、政策积累和财政资源则是边缘条件。根据条件配置差异,数字政府专项政策扩散的组态路径可进一步概括为“造势赶超”“更上层楼”“水到渠成”三种类型。相较“有力者事成”,“有志者事成”逻辑体现得更为突出。动机和能力条件的差序配置格局及政策积累的双向影响,丰富了中国政策扩散研究的场景与视角。

Machine learning molecular dynamics simulations of liquid methanol

As the simplest hydrogen-bonded alcohol,liquid methanol has attracted intensive experimental and theoretical interest.However,theoretical investigations on this system have primarily relied on empirical intermolecular force fields or ab initio molecular dynamics with semilocal density functionals.Inspired by recent studies on bulk water using increasingly accurate machine learning force fields,we report a new machine learning force field for liquid methanol with a hybrid functional revPBE0 plus dispersion correction.Molecular dynamics simulations on this machine learning force field are orders of magnitude faster than ab initio molecular dynamics simulations,yielding the radial distribution functions,selfdiffusion coefficients,and hydrogen bond network properties with very small statistical errors.The resulting structural and dynamical properties are compared well with the experimental data,demonstrating the superior accuracy of this machine learning force field.This work represents a successful step toward a first-principles description of this benchmark system and showcases the general applicability of the machine learning force field in studying liquid systems.

Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Numerical Investigations on Dynamic Stall Characteristics of a Finite Wing

The paper examines the dynamic stall characteristics of a finite wing with an aspect ratio of eight in order to explore the 3D effects on flow topology,aerodynamic characteristics,and pitching damping.Firstly,CFD methods are developed to calculate the aerodynamic characteristics of wings.The URANS equations are solved using a finite volume method,and the two-equation k-ωshear stress transport(SST)turbulence model is employed to account for viscosity effects.Secondly,the CFD methods are used to simulate the aerodynamic characteristics of both a static,rectangular wing and a pitching,tapered wing to verify their effectiveness and accuracy.The numerical results show good agreement with experimental data.Subsequently,the static and dynamic characteristics of the finite wing are computed and discussed.The results reveal significant 3D flow structures during both static and dynamic stalls,including wing tip vortices,arch vortices,Ω-type vortices,and ring vortices.These phenomena lead to differences in the aerodynamic characteristics of the finite wing compared with a 2D airfoil.Specifically,the finite wing has a smaller lift slope during attached-flow stages,higher stall angles,and more gradual stall behavior.Flow separation initially occurs in the middle spanwise section and gradually spreads to both ends.Regarding aerodynamic damping,the inboard sections mainly generate unstable loading.Furthermore,sections experiencing light stall have a higher tendency to produce negative damping compared with sections experiencing deep dynamic stall.

Oxidation behavior of ferrovanadium spinel particles in air:Isothermal kinetic and reaction mechanism

The oxidation behavior of ferrovanadium spinel(FeV_(2)O_(4)),synthesized via high-temperature solid-state reaction,was investigated using thermogravimetry,X-ray diffractometry,and X-ray photoelectron spectroscopy over the temperature range of 450–700℃.The results revealed that the oxidation process of FeV_(2)O_(4)can be divided into three stages with the second stage being responsible for maximum weight gain due to oxidation.Three classical methods were employed to analyze the reaction mechanisms and model functions for distinct oxidation stages.The random nucleation and subsequent growth(A_(3))kinetic model was found to be applicable to both initial and secondary stage.The third stage of oxidation was consistent with the three-dimensional diffusion,spherical symmetry(D_(3))kinetic mode.Both the model-function method and the model-free method were utilized to investigate the apparent activation energy of the oxidation reaction at each stage.It was found that the intermediates including Fe_(3)O_(4),VO_(2),V_(2)O_(3),and Fe_(2.5)V_(7.11)O_(16),played significant roles in the oxidation process prior to the final formation of FeVO_(4)and V_(2)O_(5)through oxidation of FeV_(2)O_(4).

Evolutionary analysis of green credit and automobile enterprises under the mechanism of dynamic reward and punishment based on government regulation

To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.

Multi-dimension and multi-modal rolling mill vibration prediction model based on multi-level network fusion

Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.

Enabling Technologies for Autonomous Robotic Systems in Manufacturing

Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.

A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

Support design method for deep soft-rock tunnels in non-hydrostatic high in-situ stress field

Due to the long-term plate tectonic movements in southwestern China,the in-situ stress field in deep formations is complex.When passing through deep soft-rock mass under non-hydrostatic high in-situ stress field,tunnels will suffer serious asymmetric deformation.There is no available support design method for tunnels under such a situation in existing studies to clarify the support time and support stiffness.This study first analyzed the mechanical behavior of tunnels in non-hydrostatic in-situ stress field and derived the theoretical equations of the ground squeezing curve(GSC)and ground loosening curve(GLC).Then,based on the convergence confinement theory,the support design method of deep soft-rock tunnels under non-hydrostatic high in-situ stress field was established considering both squeezing and loosening pressures.In addition,this method can provide the clear support time and support stiffness of the second layer of initial support.The proposed design method was applied to the Wanhe tunnel of the China-Laos railway in China.Monitoring data indicated that the optimal support scheme had a good effect on controlling the tunnel deformation in non-hydrostatic high in-situ stress field.Field applications showed that the secondary lining could be constructed properly.

Characterization of the dissociation pathways of dichloromethane and glutathione in dichloromethane dehalogenase

Dichloromethane(DCM)dehalogenase stands as a crucial enzyme implicated in the degradation of methylene chloride across diverse environmental and biological contexts.However,the unbinding pathways of ligands from DCM dehalogenase remain unexplored.In order to gain a deeper understanding of the binding sites and dissociation pathways of dichloromethane(DCM)and glutathione(GSH)from the DCM dehalogenase,random accelerated molecular dynamics(RAMD)simulations were performed,in which DCM and GSH were forced to leave the active site.The protein structure was predicted using Alphafold2,and the conformations of GSH and DCM in the binding pocket were predicted by docking.A long equilibrium simulation was conducted to validate the structure of the complex.The results show that GSH is most commonly observed in three main pathways,one of which is more important than the other two.In addition,DCM was observed to escape along a unique pathway.The key residues and protein helices of each pathway were identified.The results can provide a theoretical foundation for the subsequent dissociation mechanism of DCM dehalogenase.

Ground response and failure mechanism of gob-side entry by roof cutting with hard main roof

This study is the result of long-term efforts of the authors’team to assess ground response of gob-side entry by roof cutting(GSERC)with hard main roof,aiming at scientific control for GSERC deformation.A comprehensive field measurement program was conducted to determine entry deformation,roof fracture zone,and anchor bolt(cable)loading.The results indicate that GSERC deformation presents asymmetric characteristics.The maximum convergence near roof cutting side is 458 mm during the primary use process and 1120 mm during the secondary reuse process.The entry deformation is closely associated with the primary development stage,primary use stage,and secondary reuse stage.The key block movement of roof cutting structure,a complex stress environment,and a mismatch in the supporting design scheme are the failure mechanism of GSERC.A controlling ideology for mining states,including regional and stage divisions,was proposed.Both dynamic and permanent support schemes have been implemented in the field.Engineering practice results indicate that the new support scheme can efficiently ensure long-term entry safety and could be a reliable approach for other engineering practices.