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Self-organization has been regarded as a tool for the synthesis of well-defined organic nanostructures. Heterocyclic annulated perylene diimides are the subjects of considerable current research studies. The purpose of this study is to reveal the photophysical property, electronic structure and solid-state packing of O-heterocyclic annulated perylene diimide.

Asymmetrically five-membered O-heterocyclic annulated perylene diimide (OAPDI) was synthesized. Structure and purity of OAPDI were confirmed by ¹H NMR, ¹³C NMR, IR and mass spectral techniques. Photophysical properties of OAPDI were studied using UV–vis absorption and fluorescence in both solution (CHCl₃) and solid state. Scanning electron microscopic and atomic force microscopy were used to characterize the surface morphology of OAPDI. Conducting properties of the OAPDI were evaluated by current–voltage measurements. The compounds geometries were also optimized at 6-31G* using density functional theory.

The UV–vis absorption and fluorescence spectra of OAPDI in solution are blue-shifted in comparison with that of unsubstituted perylene bisimide. Solid-state UV–vis measurements of OAPDI indicate that it is capable of forming highly ordered structure. The non-covalent interactions, electrostatic attraction and p-p stacking moieties of OAPDI synergistically guide assembly and domain growth while maintaining the interpenetrating network of nanofibers in the solid film. The OAPDI gave higher current at −2.0 V (0.68 µA) and 4.0 V (1.0 µA).

This study will be helpful for exploring feasible routes to acquire soluble perylene diimides and well-defined organic nanostructures. Furthermore, such molecular tailoring approach would be helpful for designing and synthesizing novel organic semiconductive materials with excellent charge-transporting and light-emitting capabilities.

The nonlinear friction disturbance of the moving joint surface of the feed system can lead to the residual vibration of the system, prolong the stability time of the system and reduce the motion precision and machining precision of the machine tool. This paper aims to concern the vibration between joint surfaces caused by nonlinear friction.

The model is established from the micro and macro scale based on the LuGre model. The friction characteristics of the moving joint surface are explored. The friction experiment of GCr15 pin and 45 steel disk is designed and the influence of lubrication condition, speed, acceleration and normal load on friction characteristics are studied.

Among the drive speed, damping and stiffness, the negative gradient effect of friction, which is characterized by the difference of static and dynamic friction coefficient Δµ, is the main cause of friction vibration between moving joint surfaces. Sufficient lubrication, a proper increase of speed and acceleration, a reasonable reduction of normal load can reduce the negative gradient effect, which can weaken the vibration caused by the nonlinear friction and improve the friction characteristics of the moving joint surface.

In the past studies, more attention has been paid to revealing the relationship between the relative speed and friction, while the acceleration is often ignored. The negative gradient effect of friction is improved in this paper by changing the contact conditions. Research findings of this paper effectively improve the friction characteristics of the moving interface and provide the basis for restraining the nonlinear vibration between the moving interfaces.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2019-0476/

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

When carrying out bioremediation of water polluted by biomass‐oil, the stains which can degrade the biomass‐oil efficiently should first be found. The purpose of this paper is to describe how adopted acclimation through the isolated strains degraded efficiently, and got reaction kinetics property.

During the acclimation, the biodegradation process of biomass‐oil is accorded approximately with the first‐order reaction by the way of Sturm method which is described by measuring CO₂ volume from the microbes' production.

One kind of microbe, Aspergillus versicolor, separated from the activated sludge in the aeration tanks of paper‐mill, is found to have the advantage of biodegradation in case of biomass‐oil from rice straw by rapid thermal‐liquidizing process. The biodegradation ability could be improved in aqueous culture under neutral and acidic conditions. The optimal temperature for biodegradation of biomass‐oil is 40°C. The optimal inocula content for biodegradation of biomass‐oil was 16 vol%.

The variation of lubricity of biomass‐oil with biodegradation needs more attention.

A basic research on the growth of a strain is shown, which is helpful for the biological treatment of biomass‐oil pollution.

One kind of fungi, Aspergillus versicolor, can be used for the biodegradation of biomass‐oil. The effects of various conditions or parameters on biodegradation of biomass‐oil are discovered in aqueous culture conditions in the case of Aspergillus versicolor.

This paper examines how the level of low-carbon awareness (LCA) affects the remanufacturing strategy in a supply chain with an original equipment manufacturer (OEM) and an independent remanufacturer (IR) competing with each other.

Game theory and operations optimization.

The studies analytically characterize the threshold levels of the LCA in response to which the OEM and the IR will change their remanufacturing strategies from no remanufacturing to partial remanufacturing and then to full remanufacturing. In addition, the studies reveal that as compared with the OEM, the IR has more flexibility in terms of the market entry to remanufacturing with the level of LCA increasing. With the extended studies, it is exhibited that the above findings are robust to a good extent.

It can provide decision support for remanufacturing enterprises.

This paper aims to investigate the effect of rural-urban income gap on agricultural growth in China and its dynamics over time and across regions since reform and opening up.

Two types of indices are constructed to measure the rural-urban income gap: the intra-provincial index and the inter-provincial index. A provincial panel data from 1978 to 2010 and growth accounting method are used to estimate the size of the adverse effect of rural-urban income gap on agricultural growth in China.

The empirical results show that both indices of rural-urban income gaps are negatively associated with agriculture output, but the inter-provincial rural-urban income gap produces a larger adverse effect than the intra-provincial rural-urban income gap. Growth accounting analysis further shows that such adverse effects are decreasing over time and are larger in the central provinces. The results represent resource diversion effects of rural-urban income gap on agriculture.

This paper bridges the gap in existing literature on the relationship between sectoral income gaps and agricultural growth, which confirms Schultz's argument that agricultural activities are efficient even in developing countries and the rural resources diverted out by income gap are not surplus. The results imply that equalized rural-urban and regional policies are required to maintain sustainable agricultural growth in China.

In large-scale group decision-making (LSGDM) situations, existing TODIM group decision-making methods often fail to account for the influence of social network relationships and the bounded rationality of decision-makers (DMs). To address this issue, a new TODIM-based group decision-making method is proposed that considers the current trust relationships among DMs in a large-scale trust relationship network.

This method consists of two main stages. In the first stage, the large-scale group is partitioned into several sub-clusters based on trust relationships among DMs. The dominance degree matrix of each sub-cluster is then aggregated into the large-scale group dominance degree. In the second stage, after aggregating the large-scale group dominance degree, the consensus index is calculated to identify any inconsistent sub-clusters. Feedback adjustments are made based on trust relationships until a consensus is reached. The TODIM method is then applied to calculate the corresponding ranking results. Finally, an illustrative example is applied to show the feasibility of the proposed model.

The proposed method is practical and effective which is verified by the real case study. By taking into account the trust relationships among DMs in the core process of LSGDM, it indeed has an impact on the decision outcomes. We also specifically address this issue in Chapter Five. The proposed method fully incorporates the bounded rationality of DMs, namely their tendency to accept the opinions of trusted experts, which aligns more with their psychology. The two-stage consensus model proposed in this paper effectively addresses the limitations of traditional assessment-based methods.

This study establishes a two-stage consensus model based on trust relationships among DMs, which can assist DMs in better understanding trust issues in complex decision-making, enhancing the accuracy and efficiency of decisions, and providing more scientific decision support for organizations such as businesses and governments.

As one of the world's most productive ecosystems, ecological land plays an important role in regional and global environments. Utilizing advanced optical and synthetic aperture radar (SAR) data for land cover/land use research becomes increasingly popular. This research aims to investigate the complementarity of fully polarimetric SAR and optical imaging for ecological land classification in the eastern coastal area of China.

Four polarimetric decomposition methods, namely, H/Alpha, Yamaguchi3, VanZyl3 and Krogager, were applied to Advanced Land Observing Satellite (ALOS) SAR image for scattering parameter extraction. These parameters were merged with ALOS optical parameters for subsequent classification using the object-based quick, unbiased, efficient statistical tree decision tree method.

The experimental results indicate that an improved classification performance was obtained in the decision level when merging the two data sources. In fact, unlike classification using only optical images, the proposed approach allowed to distinguish ecological land with similar spectrum but different scattering. Moreover, unlike classification using only polarimetric information, the integration of polarimetric and optical data allows to accurately distinguish reed from artemisia and sand from salt field and therefore achieve a detailed classification of the coastal area characteristics.

This research proposed an integrated classification method for coastal ecological land with polarimetric SAR and optical data. The object-based and decision-level fusion enables effective ecological land classification in coastal area was verified.

This study aims to look into consumers' green consumption intention by incorporating social media exposure, environmental concern and habit into theory of planned behavior (TPB) in the context of China advocating green consumption.

Based on the data collected from online survey, this study use partial least squares structural equation modeling (PLS-SEM) to analysis the measurement model and structure model.

The results show attitude, social media exposure, environmental concern and subjective norms are important determinants of consumers' intention to purchase green products.

This study explores the new associations between the major constructs of the TPB model in green consumption. This study also expanded the TPB model by adding three extra factors, namely social media exposure, habit and environmental concern. In addition, this study attempts to bridge the gap between attitude and intention from a new perspective by using social media exposure as a moderating variable.

To solve the problem of low sensitivity of traditional capacitive proximity sensor, this paper aims to propose a novel capacitive sensor for detection of an approaching conductor.

Five capacitive proximity sensors with different structures are designed and the performance is compared with the traditional capacitive sensor. The impacts of geometrical parameters on the performance of the proposed capacitive sensor are studied. Furthermore, the sensitivity of the proposed capacitive sensor to an approaching conductor with different sizes is discussed. Also, how the designed capacitive sensor is sensitive to the lateral placement of the approaching object is analyzed.

Several capacitive proximity sensor structures have been designed and analyzed. It is found that the capacitive sensor with the top small ring-bottom large ring structure shows stronger electric field distribution around the top electrode and higher sensitivity to the approaching conductor than other sensors. Through further analysis of the proposed sensor, the results demonstrate that proposed capacitive sensor is effective for proximity object detection.

This paper proposes a novel capacitive proximity sensor with top small ring-bottom large ring structure. Compared with the traditional capacitive sensor, the proposed capacitive sensor is more sensitive to the approaching object. This would be helpful for the accurate detection of the approaching object. Also, the top and bottom electrodes are much smaller.