Influence Mechanism Research Articles

Influence Mechanism of Vertical Mirror Symmetry on Out-of-Plane Dielectric Properties in 2D Materials.

In vertically integrated transistor structures, understanding the out-of-plane dielectric properties of 2D materials is crucial. We performed first-principles calculations to investigate the out-of-plane dielectric properties, including electronic and ionic polarization, of three types of 2D materials: transition metal dichalcogenides MX2 (M = Mo, W; X = S, Se, Te), transition metal halide nitrides MNX (M = Ti, Zr, Hf; X = Cl, Br), and MF4 (M = Sn, Pb). We identified a suppression mechanism for ionic polarization caused by vertical mirror symmetry, which becomes more pronounced with higher structural symmetry and atomic coordination. This mechanism ultimately reduces the out-of-plane ionic contribution of 2D MX2 to nearly zero. Using the classical spring oscillator model and second-order perturbation theory, we identified relevant physical quantities to specifically analyze the variation of the dielectric constant. This study provides a framework for analyzing 2D materials' dielectric properties and guides the design of novel dielectric materials.

Influence of Rejuvenation Heat Treatment on Creep Property for Nickel-Based Directionally Solidified Superalloy

Creep is one of the most typical failure modes for the turbine blades of an aero-engine. The microstructure of the turbine blades after long-term service can be adjusted by rejuvenation heat treatment (RHT) to restore its creep properties. In this work, a series of RHT experiments were carried out on a directionally solidified (DS) nickel-based superalloy under different solution temperatures and primary aging temperatures based on the standard heat treatment (SHT) process parameters to investigate the mechanism of temperature influence on DS’s microstructure after RHT. It is indicated that a more uniform microstructure can be obtained under higher solution temperatures and lower primary aging temperatures compared to the SHT process. Furthermore, by employing the image processing methods to quantify microstructural parameters, a comprehensive indicator parameter for the RHT effect (marked as Prej) was proposed to characterize the effects of RHT on DS superalloy’s microstructure and creep property combined with the entropy weight method. Based on this, a regression model to describe the relationship between RHT process parameters and Prej was constructed by using the response surface methodology (RSM). It is revealed that the optimal solution temperature and primary aging temperature for this DS superalloy are 1283 °C and 1095 °C, respectively. Then the conclusion was validated through complete creep experiments on the DS superalloy, which showed the creep life after RHT reaches 95.5% of the SHT specimen, and the total life has increased by 20.6%.

Can Agricultural Subsidies Reduce Cropland Abandonment in Rural China?

Cropland abandonment has significant implications for sustainable agricultural development. Whether agricultural subsidies can reduce cropland abandonment is correlated with China’s food security. Relying on the China Labor-force Dynamics Survey (CLDS) data and the two-way fixed effects model, this study investigates the implications of agricultural subsidies on cropland abandonment and its influence mechanism. The results demonstrate that agricultural subsidies effectively reduce cropland abandonment, which is robust after robustness and endogeneity tests. Mechanism analysis indicates that agricultural subsidies inhibit cropland abandonment by incentivizing farmers to increase agricultural production inputs and facilitate cropland transfer. Heterogeneous analysis reveals that agricultural subsidies yield more significant benefits in eastern and central regions and plain and hill areas, particularly among households with higher degrees of part-time employment. Moreover, the effect of agricultural subsidies on cropland abandonment is greater in households with higher levels of population aging. These findings complement existing research on the impact of agricultural subsidies on agricultural production and offer valuable insights for policymakers devising strategies to curb cropland abandonment and foster sustainable agricultural development.

Unwilling or Unable? The Impact of Role Clarity and Job Competence on Frontline Employees’ Taking Charge Behaviors in Hospitality Industry

Hotels expect front-line staff to demonstrate greater flexibility and proactively take on more responsibility beyond their job duties, which helps to provide better customer service in an environment of uncertainty and change. Accordingly, employees’ taking charge behaviors have received widespread attention in academia and practice. Through a three-wave online survey of 352 front-line employees and their supervisors from 13 high-star hotels in the Greater Bay Area of China, this study examined the influence mechanisms of role clarity and job competence on the employees’ taking charge behavior and the moderating effect of supervisor developmental feedback. The findings indicate that frontline employees’ role clarity and job competence can enhance taking charge behavior by increasing their organization-based self-esteem. It empirically validates Proactive Motivation Theory and clarifies that employees’ proactive engagement in extra-role responsibilities depends not only on their willingness but also on sufficient competence and a clear understanding of their job roles. Supervisor developmental feedback is more acceptable to employees as a form of informational support and can enhance the impact of role clarity and job competence on frontline employees’ taking charge behaviors.

The Influence Mechanism and Intervention Path of Self-concealment Psychology on Campus Bullying of College Students.

As a long-term problem of campus governance at home and abroad, the high incidence of campus bullying and the potential risk of physical and mental harm need to be studied from a new perspective. The study found that excessive self-concealment will significantly increase the degree of bullying, and further weaken the social support network of the bullied. To adjust self-concealment psychology as a new strategy to prevent and control campus bullying, it is necessary to break the vicious circle between self-concealment and bullying, improve the self-cognition of college students, and actively cope with the phenomenon of campus bullying.

Exploring the factors determining fintech adoption among Indian users integrating ‎Theory of Planned Behaviour ( TPB) and Social Learning Theory (SLT)‎

Even though the number of Financial Technology (Fintech) services is on the rise, the ‎behavioural and psychological factors of how the user’s intent remains to a key focus point ‎of research. (In 2020, Rahardjo et al.) This research proposes a comprehensive model for ‎understanding Fintech adoption in India, integrating the Theory of Planned Behaviour (TPB) ‎and Social Learning Theory (SLT). The three TPB constructs, attitude, Subjective norms, and ‎perceived behavioural control (PBC), serve as key determinants of behavioural intention ‎‎(Gao, Y., & Tang, Y., 2023). Conversely, SLT enhances this paradigm by incorporating ‎elements of social influence, observational learning, and reinforcement mechanisms, thus ‎bringing to light how consumers come to establish confidence and trust in ‎Fintech services. By incorporating various theoretical perspectives, this study aims to provide a comprehensive understanding of the influence of social and individual ‎ factors on consumer intentions towards Fintech adoption, as these factors interact in determining behavior. The study is quantitative using survey data from 462 sample responses ‎analysed using Structural Equation Modelling (SEM) through AMOS software. The findings suggest that although social influence and observational learning are key factors influencing user perceptions, both attitude and perceived behavioural control are significantly influential on behavioral intention. Also, intention mediated the relationship between TPB constructs ‎and adoption of Fintech services, while privacy risk moderated the relationship between ‎intention and adoption in digital financial services. These findings emphasize how social ‎learning dynamics, techniques of trust-building are promoting Fintech acceptance among ‎Indian users. This research enhances existing knowledge by incorporating behavioural and ‎psychological viewpoints and is beneficial for financial institutions, legislators, and Fintech ‎firms who seek to promote the usage of digital financial services‎.

Spatial Heterogeneity of Soil Respiration and Its Relationship with the Spatial Distribution of the Forest Ecosystem at the Fine Scale

Forest soil respiration plays a crucial role in the global carbon cycle. However, accurately estimating regional soil carbon fluxes is challenging due to the spatial heterogeneity of soil respiration at the stand level. This study examines the spatial variation of soil respiration and its driving factors in subtropical coniferous and broad-leaved mixed forests in southern China, aiming to provide insights into accurately estimating regional carbon fluxes. The findings reveal that the coefficient of variation (CV) of soil respiration at a scale of 50 m × 50 m is 18.82%, indicating a moderate degree of spatial variation. Furthermore, 52% of the spatial variation in soil respiration can be explained by the variables under investigation. The standardized total effects of the main influencing factors are as follows: soil organic carbon (0.71), diameter at breast height within a radius of 5 m (0.31), soil temperature (0.27), and soil bulk density (−0.25). These results imply that even in relatively homogeneous areas with flat terrain, fine-scale soil respiration exhibits significant spatial heterogeneity. The spatial distribution of woody plant resources predominantly regulates this variation, with root distribution, shading effects, and changes in soil physical and chemical properties being the main influencing mechanisms. The study emphasizes the importance of simulations at different microscales to unravel the potential mechanisms governing macroscopic phenomena. Additionally, it highlights the need for incorporating a more comprehensive range of variables to provide more meaningful references for regional soil carbon flux assessment.

Influence mechanism of process parameters on axial compressive response of CNTs reinforced filament‐wound riser with metal liner

AbstractCarbon nanotubes (CNTs) reinforced filament‐wound riser with metal liner face critical challenges in maintaining structural integrity under axial compressive loads, especially when subjected to the harsh conditions of deep‐sea environments. However, existing manufacturing processes for filament winding risers lack a comprehensive understanding of how key process parameters interact to influence axial compressive strength. This study aims to deeply explore the influence mechanism of process parameters on the axial compressive strength of CNTs reinforced filament‐wound riser with metal liner. The compressive strength model was constructed by using the multivariate nonlinear method, and the effectiveness of the model was ensured through verification. Meanwhile, the influence mechanism of a single process parameter was analyzed to reveal the internal relationship between the winding tension, feed rate, curing time, and the maximum axial compressive load. The coupling effects of process parameters were analyzed to elucidate the mechanism by which parameter interactions govern compression performance. Furthermore, the sensitivity analysis was carried out to determine the key sensitive parameters, divide the process window, and optimize the parameters. Finally, the optimal process parameters combination with the maximum axial compressive load of 88.4074 kN, 51.7448 N of winding tension, 14.8607 m/min of winding speed, and 6.3741 h of curing time was determined based on the PSO‐GWO algorithm. The research results can provide a novel approach for the manufacturing of high‐performance deep‐sea risers.Highlights Novel approach integrating multiple nonlinear regression and global–local sensitivity analysis. Stable region division method was adopted to determine the optimal ranges for composite wound risers. PSO‐GWO hybrid algorithm was employed to optimize the CNTs reinforced composite process parameters.

Study on the instability characteristics and influencing mechanism of coal-rock parting-coal structure under triaxial loading

Rockburst accidents are highly likely to take place during the mining of coal seams in bifurcated area. A conventional triaxial testing machine and an acoustic emission (AE) monitoring system are employed to investigate the failure and instability characteristics of coal-rock parting-coal structure (CRCS) and its influencing mechanism. The results show that: (1) The instability process of the composite structure under the conventional triaxial path represents a coupled instability process of contact surface slipping and coal/rock fracture. The penetration of tensile fractures into shear fractures serves as the primary cause of the overall instability of the composite structure. (2) Alterations in the main frequency and maximum amplitude, a sharp decrease in the radiant energy index, and a significant increase in the cumulative apparent volume can be utilized as precursor identification information of the slipping and overall instability of the composite structure. (3) The inclination angle of the contact surface, confining pressure, and loading speed have an impact on the instability of the composite structure. Effectively controlling these factors during production can contribute to reducing the risk of impact disasters. The research results can provide theoretical support for the early warning and prevention of rockburst accidents in the bifurcated area.

Monitoring Plateau Pika and Revealing the Associated Influencing Mechanisms in the Alpine Grasslands Using Unmanned Aerial Vehicles

Plateau pika (Ochotona curzoniae, hereafter pika) is a key species in the alpine grasslands on the Qinghai-Tibetan Plateau (QTP). They are susceptible to the influence of external disturbance and may present great variation, which is important to evaluate their ecological role in alpine grasslands. However, our knowledge regarding their interannual variation and the influencing mechanism is still limited due to the lack of long-term observation of pika density. This study aimed to investigate the spatiotemporal variations in pika and the associated key influencing factors by aerial photographing at 181 sites in Gannan Tibetan Autonomous Prefecture in 2016, 2019, and 2022. Our findings showed that: (1) pika primarily distributed in the central and northeastern Maqu County and the southwestern part of Luqu County, and their average density was in a range of 9.87 ha−1 to 14.43 ha−1 from 2016 to 2022; (2) high pika density were found in 1.22 to 3.61 °C for annual mean temperature, 12.86 to 15.06 °C for diurnal temperature range, 3400 to 3800 m for DEM and less than 3° for slope; and (3) pika density showed varied response to interannual changes in mean diurnal range, annual precipitation and precipitation of the driest month in different years. Our results concluded that pika density showed significant spatiotemporal variations, and climate and terrain variables dominantly affected pika density. Given the great interannual fluctuation of climate variables and different responses of pika density to these variables, our results suggested that long-term monitoring of pika is crucial to reveal their real distribution, response mechanism to habitat environment, and role in alpine grasslands. Moreover, unmanned aerial vehicles are cost-effective tools for the long-term monitoring of pika.

Multi-governance paths of BIM promotion based on fsQCA

Purpose The global architectural, engineering and construction field has greatly benefited from the use of building information modeling (BIM) owing to its high quality, efficiency and sustainability. The practical effect of BIM promotion in the region is unsatisfactory, despite vigorous government support and industry needs. Policy has been regarded as one of the most important drivers for promoting BIM. Existing research mainly focuses on the influences of policy instruments on BIM promotion but fails to reveal their underlying logics and match them locally adapted, limiting their guidance in practice. This study aims to address this research gap by optimizing the path of BIM promotion from the perspective of policy combinations. Design/methodology/approach Policy goals and policy instruments are first identified based on 152 BIM promotion policies issued in China. This paper develops a two-dimensional framework of “policy goals-policy instruments.” The influence mechanisms of policy instrument combinations on BIM promotion are further revealed using fuzzy-set qualitative comparative analysis (fsQCA). Findings The results show that none of the five policy goals, including enhancing BIM technology application capabilities (FP1), are regarded as core conditions influencing BIM promotion levels (Y). Four configurations were identified, reflecting the four types of BIM multigovernance paths, namely, H1, H2, H3 and H4. Regions with varying developmental contexts will adopt distinct configurations and tailor their BIM promotion strategies accordingly, which may involve overcoming challenges in BIM technology innovation, cultivating BIM talent, enhancing BIM promotion and publicity and integrating BIM with other technologies. Originality/value This paper expands on the application of fsQCA in the context of BIM governance paths. The results provide valuable initial insights for policymakers in different regions, helping to address regional imbalances in BIM promotion and facilitating the construction industry’s transition toward greater intelligence and sustainability.

A review of the effects of different resistance training prescriptions on cognitive function in older adults

BACKGROUND: The effects of resistance training on brain structure and cognitive functioninolder adults have now received widespread attention, but the effectiveness of the interventionandthe related mechanisms of influence require an exercise prescription dose relationship perspectivein order to make a comprehensive judgement on its benefits and many controversies. METHODS: A literature review was used to explore the effects of different resistancetrainingmethods on the brain and cognitive function of older adults, with the help of PubMed, Springerand Web of Science (Core Collection) databases to collect and collate resistance trainingrelatedliterature, search keywords include: resistance training prescription; cognitive function;prescription dosage; functional resistance training; older adults. RESULTS: High total training volume and medium to high intensity resistance trainingmaybemore effective in enhancing executive function; different resistance training modes, especiallyunstable plane resistance training and high-speed resistance training, are effective inenhancingcognitive function in middle-aged and elderly populations; complex and challengingresistancetraining or cognitive work-intervention resistance training are more positive for cognitiveimprovement in older adults. CONCLUSION: Training at least twice a week, as well as complex, challenging trainingwithtraditional or modified modalities, may contribute to cognitive function; there is no consensusonthe optimal total amount of resistance training, rest periods, and training modalities for differentpopulations, and further in-depth discussion is needed in the future.

The Influence Mechanism of Sci-Tech and Finance Integration Policies on New-Quality Productivity in Chinese Cities - Based on DID Model

In the era of knowledge economy, technological progress is a key measure of national strength and a focal point of competition among nations. This paper utilizes data from 285 prefecture-level cities in China from 2009 to 2019, employing the Difference-in-Differences (DID) method to study the impact of policies combining technology and finance on local new quality productivity. The research indicates that the effective integration of technology and finance observably enhances the new quality productivity of prefecture-level cities, mainly achieved by improving regional innovation capabilities and optimizing industrial structures. Heterogeneity tests show that the impact of this integration varies across different regions, with more developed areas benefiting more, while less developed areas experience a lag effect. This may be related to factors such as regional resources, financial infrastructure, and types of industries. Further research will delve into the reasons for these differences and conduct mediation-heterogeneity analysis to propose more effective policy measures.

Evaluating the effect of steel slag dosage and carbonation on super sulfate cement.

Evaluating the effect of steel slag dosage and carbonation on super sulfate cement.

Effect of DC-GVS on resting functional EEG networks in healthy people.

To establish a resting state functional network based on electroencephalogram (EEG) signals and explore the effects of different intensities of direct current (DC) Galvanic Vestibular Stimulation (GVS) on healthy people. Furthermore, from the perspective of EEG connectivity and topological structure, the mechanism of DC GVS's influence on the connectivity of vestibular related nerve functions was studied. the subjets were given DC GVS stimulations which indensities are one time pain threshold, two times pain threshold and four times pain threshold. Sham stimulation was applied to be the control group. EEG signals after stimulation were collected in every group. ThewPLI method was used to construct the correlation matrix, and though setting the threshold value to construct the binary matrix. The brain network topology parameters that solved by binary matrix were analyzed to explore the impact of GVS with different intensities.Results: DC GVS stimulation of one-time threshold, two-times threshold and four-times threshold can change the brain network connection and the topological properties of the brain network. And the effect of two-times threshold GVS stimulation is the most significant. GVS with different intensities on healthy people could improve the efficiency of information transmission in different brain regions, increase the speed of information transmission, and enhance the strength of functional connectivity.It provides a theoretical reference for the neural effects of GVS from the perspective of brain functional network.

Physical Model for Thermal Stress‐Induced Phase Transition of Octogen in Polymer‐bonded Explosives

ABSTRACTThe β→δ phase transition of cyclotetramethylene tetranitramine (octogen, HMX) significantly impacts the thermal and impact safety of HMX‐based polymer‐bonded explosives (PBXs). HMX demonstrates varying phase transition temperatures when combined with different additives. To date, there has been a lack of systematic research regarding the mechanisms by which additives influence these transition temperatures. This study investigates the phase transition temperature of HMX within PBXs using X‐ray diffraction (XRD) techniques. A mathematical model has been developed to describe the interactions between the binder and HMX, effectively elucidating the underlying influence mechanisms. The predicted phase transition temperatures align closely with the results obtained from XRD analysis. It was observed that HMX crystals and additives undergo expansion upon heating, leading to alterations in the phase transition temperatures of HMX induced by thermal stress. Additionally, a physical model has been constructed to account for the phase transitions induced by thermal stress.

Nonlinear Waveform Optimization for Enhanced Ink Droplet Formation in Material Jetting

Material jetting, as a critical additive manufacturing technology, relies on precise control of the driving waveform to achieve high-quality droplet formation. During the droplet ejection process, pressure fluctuation at the nozzle outlet plays a significant role in droplet formation. Traditional experimental methods for optimizing the driving waveform often struggle to address the complex nonlinearities inherent in the jetting process. In this study, a numerical simulation model of the droplet ejection process is established to elucidate the influence mechanism of nozzle outlet pressure oscillations on droplet formation. A novel optimization method combining Convolutional Neural Networks (CNNs) and Particle Swarm Optimization (PSO) is proposed, targeting the suppression of residual pressure oscillations and achieving the desired pressure fluctuation. The method leverages nonlinear regression and optimization to obtain the optimal waveform design. Simulation and experimental results demonstrate that the optimized waveform effectively suppresses residual pressure oscillations, significantly improves droplet formation quality, and reduces pressure fluctuation convergence time by approximately 32.19%. The findings demonstrate that the optimized waveform effectively improves droplet ejection quality and stability.

A Comprehensive Robustness Analysis of Grid-Forming Virtual Synchronous Machine Systems for the Evaluation of Frequency Performance

This research proposes a robustness analysis model for the frequency performance of grid-forming converter systems (GFMCS). Based on the derived sensitivity and complementary sensitivity functions, a system robustness identification framework is established. This framework includes two key frequency performance indices: sensitivity and robust stability. Sensitivity analysis is used to describe the system’s sensitivity to external disturbances. In addition, the judgment criterion is proposed to quantitatively and intuitively identify the robustness of the GFMCS. Furthermore, the influence mechanisms of the damping and inertia coefficients on robustness are examined comprehensively. This study finds that when the damping coefficient is small, and the inertia coefficient is large, the system is more prone to oscillatory instability, resulting in longer stability time as well as poorer robustness. Finally, the theoretical analysis is validated experimentally.

Drying characteristics and numerical simulation of tissue paper

Abstract This study aims to investigate the drying process of tissue paper in depth and to analyze it comprehensively by combining experimental and simulation methods. In the experimental part, a variety of drying conditions were designed, including different air temperatures, air velocities, and bottom heating temperatures, to accurately measure the change in moisture ratio of tissue paper. Meanwhile, a mathematical model for predicting the tissue drying moisture ratio was constructed based on the experimental data, and the tissue drying process was simulated. The simulation presented the process of moisture transfer within the tissue paper visually and quantitatively. The experimental and simulation results validate and complement each other, revealing the synergistic influence mechanism of drying parameters on the drying effect of tissue paper. The results showed that the effects of air temperature, bottom heating temperature, and air velocity on the drying rate of tissue paper were in the following order: bottom heating temperature > air temperature > air velocity, and among eight drying kinetic models, the Aghbashlo model was the most suitable for describing the drying characteristics of tissue paper in thin layers, and the accuracy of the prediction model was verified by simulation.

Influence Mechanism of "Production-Living-Ecological" Spatial Evolution on Carbon Sequestration and Emission in the Shiyang River Basin

"Production-Living-Ecological" spatial linkage carbon reduction is an important starting point to realize the "carbon peaking and carbon neutrality" strategy. Exploring the influence mechanism of "Production-Living-Ecological" spatial evolution on carbon sequestration and emission is an important foundation to promote regional carbon neutrality and sustainable development. This study undertook the Shiyang River Basin as the research area. It aimed to identify the production, living, and ecological space on the basis of analyzing the evolutionary characteristics of land use pattern and analyze the "Production-Living-Ecological" spatial evolution characteristics and spatial and temporal evolutionary characteristics of carbon sequestration and emission by using related model methods. Furthermore, it discussed the influence mechanism of "Production-Living-Ecological" spatial evolution on carbon sequestration and emission by means of a geographically weighted regression model. The results showed that the area of the unused land in the Shiyang River Basin changed the most from 2000 to 2020, with a decrease of 531.5 km2. During the study period, the dynamic attitude of construction land changed the most, which was closely related to the rapid urbanization and construction of various developmental zones and ecological resettlement areas. From 2000 to 2020, the transformation of ecological structure of production and life in the Shiyang River Basin was mainly characterized by the mutual transformation of production and ecological space, followed by the mutual transformation of production and living space. During the study period, the carbon sequestration in the Shiyang River Basin was at a low level but showed a slow and gradual increasing trend, whereas the overall spatial distribution pattern was gradually decreasing from Qilian Mountain in the southwest to the northeast. The carbon emissions of the Shiyang River Basin showed a significant increasing trend, whereas the overall spatial distribution pattern was "low in the north and south and high in the middle." A significant correlation was observed between the spatial evolution of production, life, and ecology and that of carbon sequestration and emission in the Shiyang River Basin from 2000 to 2020. These results provide scientific basis for optimizing the spatial structure of land and formulating the regional "double carbon" development plan.