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The maturity of artificial intelligence technology and the emergence of AI-generated content (AIGC) tools have endowed college students with a human-AIGC tools collaboration learning mode. However, there is still a great controversy about its impact on learning effect. This paper is aimed at investigating the impact of the human-AIGC tools collaboration on the learning effect of college students.

In this paper, a hypothesized model was constructed to investigate the effects of dependence, usage purpose, trust level, frequency, and proficiency of using AIGC tools on the learning effect, respectively. This paper distributed questionnaires through random sampling. Then, the improved Analytic Hierarchy Process (AHP) was used to assign weights and normalize data. Lastly, one-way ANOVA and multiple linear regression analyses were used to measure and analyze variables, revealing the mechanism of influence.

The usage purpose, frequency, and proficiency of using AIGC tools have a significant positive effect on learning. Being clear about the usage purpose of AIGC tools and matching the specific study tasks will enhance the learning effect. College students should organically integrate AIGC tools into each learning process, which is conducive to building a learning flow applicable to oneself, improving efficiency, and then enhancing learning effects. The trust level in AIGC tools is significant, but positively and weakly correlated, indicating that college students need to screen the generated content based on their knowledge system framework and view it dialectically. The dependence on AIGC tools has a negative and significant effect on learning effect. College students are supposed to systematically combine self-reflection and the use of AIGC tools to avoid overdependence on them.

Based on the findings, the learning suggestions for college students in human-machine collaboration in the AIGC era are proposed to provide ideas for the future information-based education system. For further research, scholars can expand on different groups, professions, and fields of study.

Previous studies have focused more on the impact of AIGC on the education system. This paper analyzed the impact of the various factors of using AIGC tools in the learning process on the learning effect from the perspective of college students.

Based on the dynamic capability theory, our study tries to explore the mediator mechanism of service supply chain dynamic capability between market orientation and service innovation performance, as well as the boundary conditions in which service supply chain dynamic capability plays a role, in order to reveal the key elements and their mechanisms for manufacturing enterprises to improve service performance.

With a total of 317 valid questionnaires, structural equation modeling (SEM) was used to test the research model and hypotheses.

The empirical results confirm that the three types of service supply chain dynamic capability (environment insight capability, resource integration capability and resource reconfiguration capability) can partially mediate the relationship between firm market orientation (responsive and proactive market orientations) and service innovation performance. In addition, supply chain collaboration has different types of moderator effects on the relationship between the three types of service supply chain dynamic capability and service innovation performance.

This research discovers that market orientation and dynamic capability are the key factors leading to high service performance and reveals the mediating role of service supply chain dynamic capability between market orientation and service innovation performance. Moreover, this research explores the moderating role of supply chain collaboration in service supply chain resource reconfiguration capability and service innovation performance.

This article intends to explore the sustainability accounting practices that emerge from the business of artificial forestry in the Qingshui River society of southwest China in the 18th-19th centuries.

Using a historical approach, we set out to discuss the systematic use of “folk contract” as a tool of tracing accountability in timber trading and in the collective management of community forests in this region, based on the archives of Qingshui River Manuscripts.

The findings indicate that active transactions of small forest plots facilitated by the prevalent use of folk contracts allow both the landlords and the tenants to easily acquire cashflow needed any time before the harvest, and in turn prevent premature logging and deforestation for crop farming. An “open ledger” bookkeeping system emerged from the extensive contracting practices guarantees the functioning of a dualistic accountability system, where both market value of timbers and “face” value of community members' reputation are preserved for long-term sustainability of local economy, society and ecological environment.

From the perspective of economic anthropology, this study forms the link between the folk contract practice in sustainable forestry of the Qingshui River society and the emancipatory accounting literature.

The purpose of this paper was to comprehensively understand the effects of imidization process on the structure and properties of polyimide (PI) films through the preparation and characterization of a variety of PI/aluminium oxide (Al₂O₃) nanocomposite films by using several imidization-based strategies.

Poly(amic acid) (PAA) containing different amounts of inorganic materials (namely, 0 Wt.%, 4 Wt.%, 8 Wt.%, 12 Wt.% and 16 Wt.%) was synthesized by using pyromellitic dianhydride and 4,4-diaminodiphenyl ether as raw material and N,N-dimethylacetamide as solvent. Subsequently, the solution obtained was casted on a glass substrate and dried by the means of various curing processes. The micro-structure, Fourier transform–infrared spectral features, breakdown field strength, dielectric properties and the corona-resistant time parameters of films were achieved.

The imidization process influences substantially the properties of composite films. Therefore, as the imidization rate is increased, the corona-resistant time and the electrical breakdown strength of composite films are also improved, while the dielectric constant faces a+ decreasing.

In this paper, the impact of imidization process on the performance of PI/nano-Al₂O₃ three-layered composite film is reported. However, there are multiple factors governing these systems (such as, interlayer thickness ratio and humidity), which are not discussed herein.

The current study expounds the relationship between imidization ratios as well as the effect of imidization ratio on the performance of the film.

The dispersity of graphene oxide (GO) has an important effect on the properties of epoxy resin (EP) composites. Many modification and dispersion methods require the use of inert solvents which do not participate in the modification reaction, although GO can be uniformly dispersed in water and alcohol solvents. Based on this requirement, several inert solvents were selected as dispersion solvents to find out the suitable inert solvent for GO dispersion into EP matrix.

Several inert solvents with different solubility parameters were selected as dispersion solvents to prepare GO/EP composite. The microstructure, mechanical properties, insulation properties, dielectric properties and thermal property of the composite were characterized, which was due to find suitable inert solvent for GO dispersion into EP matrix.

The dispersity of N, N-dimethylformamide (DMF) was the best stable suspension state when it was used as solvent instead of occurring sedimentation and agglomeration. Moreover, DMF was further confirmed as a suitable inert solvent for the dispersion of GO into EP according to the mechanical properties, insulation properties and thermal conductivity characterization.

The dispersion of GO in solvents has already been researched, but the traditional solvents, such as alcohols and water, has shown their limitations with the increase of modification methods, which were not suitable for the modification environment such as cyanate graft modification. Therefore, it was very important to choose a kind of inert solvent for dissolving EP matrix and dispersing GO better.

Several inert solvents were used to disperse GO into EP, and the influence of different dispersing solvents on the adhesive was discussed through the analysis of the mechanical properties, insulation properties and thermal conductivity, which was due to explore the inert solvent suitable for GO dispersion.

Epoxy resin (EP) is a kind of thermosetting resin, and its application is usually limited by poor toughness. In this case, a type of new flexible chain blocking hyperbranched polyester (HBP) was designed and synthesized. The purpose of this study is to enhance the toughness and dielectric properties of EP.

P-toluene sulfonic acid was used as the catalyst, with dimethy propionic acid as the branch unit and pentaerythritol as the core in the experiment. Then, n-hexanoic acid and n-caprylic acid were, respectively, put to gain HBP with a n-hexanoic acid and n-caprylic acid capped structure. The microstructure, mechanical properties, insulation properties and dielectric properties of the composite were characterized for the purpose of finding the appropriate proportion of HBP.

HBP enhanced the toughness of epoxy-cured products by interpenetrating polymer network structure between the flexible chain of HBP and the EP molecular chain. Meanwhile, HBP reduced the ε and tgδ of the epoxy anhydride-cured product by reducing the number of polar groups per unit volume of the EP through free volumes.

Yet EP is a kind of thermosetting resin, which is widely used in coating, aerospace, electronics, polymer composites and military fields, but it is usually limited by poor toughness. In a word, it is an urgent priority to develop new EP with better toughness and mechanical properties.

At present, HBP has been applied as a new kind of toughening strategy and as a modifier for EP. According to the toughening mechanism of HBP modified EP, the free volume of HBP creates a space for the EP molecule to move around when loaded. Moreover, the free volume could cause the dielectric constant of EP to diminish by reducing the content of polarizable groups. Meanwhile, the addition of HBP with flexible chains grafted to the EP could develop an interpenetrating network structure, thus further enhancing the toughness of EP

The purpose of this paper is to identify corrosion types and corrosion transitions by a novel electrochemical noise analysis method based on Adaboost.

The corrosion behavior of Q235 steel was investigated in typical passivation, uniform corrosion and pitting solution by electrochemical noise. Nine feature parameters were extracted from the electrochemical noise data based on statistical analysis and shot noise theory. The feature parameters were analysis by Adaboost to train model and identify corrosion types. The trained Adaboost model was used to identify corrosion type transitions.

Adaboost algorithm can accurately identify the corrosion type, and the accuracy rate is 99.25%. The identification results of Adaboost for the corrosion type are consistent with corroded morphology analysis. Compared with other machine learning, Adaboost can identify corrosion types more accurately. For corrosion type transition, Adaboost can effectively identify the transition from passivation to uniform corrosion and from passivation to pitting corrosion consistent with corroded morphology analysis.

Adaboost is a suitable method for prediction of corrosion type and transitions. Adaboost can establish the classification model of metal corrosion, which can more conveniently and accurately explore the corrosion types. Adaboost provides important reference for corrosion prediction and protection.

The purpose of this paper is to research the induced flashover laws of different insulation materials under electrostatic electromagnetic pulse, and the induced flashover characteristics of different electrode structures are further explored.

According to standard IEC 61000–4-2, an experimental system of electrostatic electromagnetic pulse flashover for insulation materials is established. The induction flashover laws of polytetrafluoroethylene, epoxy resin and polymethyl methacrylate surface-mounted finger electrodes under the different intensity of electrostatic electromagnetic pulse are researched. The influence of the finger electrode, needle–needle electrode and needle–plate electrode on insulation flashover was compared. Secondary electron emission avalanche (SEEA) and field superposition theory are used to analyze the experimental results of electrostatic electromagnetic pulse induced flashover.

The larger the dielectric strength of insulation materials, the more difficult flashover occurs on the surface. The field superposition enhances collision ionization between electrons and gas molecules, which leads to the insulation materials surface induced flashover easily by electrostatic electromagnetic pulse. The sharper the electrode shapes on the insulation materials surface, the stronger the electric field intensity at the cathode triple junction, more initial electrons are excited to form the discharge channel, which easily leads to flashover on the surface of the insulating material.

The proposed field superposition combined with the SEEA method provides a new study perspective and enables a more rational, comprehensive analysis of electrostatic electromagnetic pulse induced flashover of insulation materials. The work of this paper can provide a reference for the safety protection of spacecraft in orbit under a strong electromagnetic field environment, increase the service life of spacecraft and improve the reliability of spacecraft’s safe operation in orbit. It provides a basis for the selection of insulation materials for equipment under the different intensities of the external electromagnetic environment.

This paper aims to explore question and answer (Q&A) participation and behavioral patterns on academic social networking sites (ASNSs) from the perspective of multiple subjects such as academic, corporate and government institutions.

Focused on the Q&A service of ASNSs, this study chooses ResearchGate (RG) as the target ASNS and collects a large-scale data set from it, involving a sample of users and a Q&A sample about academic, corporate and government institutions. First, it studies the law of Q&A participation and the distribution of the type of user according to the sample of users. Second, it compares question-asking behavior and question-answering behavior stimulated by questions among the three types of institutions based on the Q&A sample. Finally, it discusses the Q&A participation and behavioral patterns of the three types of institutions in academic Q&A exchanges with full consideration of institutional attributes, and provides some suggestions for institutions and ASNSs.

The results show that these three types of institutions generally have a low level of participation in the Q&A service of RG, and the numbers of questions and answers proposed by institutional users conform to the power-law distribution. There are differences in Q&A participation and Q&A behavioral patterns among academic, corporate and government institutions. Government and academic institutions have more users participating in the Q&A service and their users are more willing to ask questions, while corporate institutions have fewer users who participate in the Q&A service and their users are inclined to provide answers. Questions from corporate institutions attract much more attention than those from the other two types of institutions.

This study reveals and compares the Q&A participation and the behavioral patterns of the three types of institutions in academic Q&A, thus deepening the understanding of the attributes of institutions in the academic information exchange context. In practice, the results can help guide different institutions to use the Q&A service of ASNSs more effectively and help ASNSs to better optimize their Q&A service.

The purpose of this paper is to provide a quantitative assessment on the effect of wall roughness on the pressure drop of fluid flow in microchannels.

The wall roughness is generated by the method of random midpoint displacement (RMD) and the lattice Boltzmann BGK model is applied. The influences of Reynolds number, relative roughness and the Hurst exponent of roughness profile on the Poiseuille number are investigated.

Unlike the smooth channel flow, Reynolds number, relative roughness and the Hurst exponent of roughness profiles play critical roles on the Poiseuille number Po in rough microchannels. Modeling results indicate that, in rough microchannels, the rough surface configuration intensifies the flow-surface interactions and the wall conditions turn to dominate the flow characteristics. The perturbance of the local flows near the channel wall and the formation of recirculation regions are two main features of the flow-surface interactions.

The fluid flow in parallel planes with surface roughness is considered in the current study. In other words, only two-dimensional fluid flow is investigated.

The LBM is a very useful tool to investigate the microscale flows.

A new method (RMD) is applied to generate the wall roughness in parallel plane and LBM is conducted to investigate the pressure drop characteristics in rough microchannels.