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This paper aims to explore the influence of the reinforcement included either glass beads (GBs) or carbon fiber (CF) on the reinforced polyamide 12 (PA12) composite samples prepared by selective laser sintering (SLS).

In this paper, the microstructure and mechanical properties are investigated, and the results are compared with those obtained for non-reinforced pure PA12 samples prepared by SLS.

The tensile fracture surface of the non-reinforced pure PA12 sample presents strong micro-deformation within the crack origination zone between the melted PA12 matrix and the un-melted PA12 particle cores. As a result, the pure PA12 sample exhibits the greatest maximum elongation. The maximum tensile strength is obtained for the CF reinforced sample because of the strengthening effect of CF and the relatively good bonding between CFs and the PA12 matrix. The minimum tensile strength is obtained for the GB reinforced PA12 sample because of the relatively weak bonding between GBs and the PA12 matrix.

These results demonstrate that the characteristics of the interfaces between the reinforcement and the PA12 matrix have an important influence on the fracture mechanisms and mechanical properties of PA12 composites fabricated by SLS.

Legislation plays a vital role in solving carbon emissions reduction and climate change issues. China began to implement a low-carbon economic policy in 2010, but the effect of the policy needs to be evaluated. Accordingly, this paper aims to discuss China’s low-carbon policy through exploring the following two questions, namely, whether the policy effect reaches the expected goal and whether the policy effects will balance economic development and emission reduction. Then, the paper puts forward suggestions for the improvement of China’s low-carbon policy.

This paper is organized around three distinct aspects of policy effect evaluation. This paper uses the synthetic control method to construct a policy effect evaluation model and conducts a quasi-natural experiment. The paper selects annual panel data from 2003 to 2015, which is selected from 33 provinces. A comparative analysis of carbon dioxide emissions, energy consumption and economic development between Hubei Province and Liaoning Province.

The results reveal that the implementation of the low-carbon pilot province policy in 2010 has a significant impact on the emission reduction effect of Liaoning Province, but the impact on the emission reduction effect of Hubei Province is not significant. The carbon emission trading system implemented in 2012 has reduced the emission reductions in Hubei Province and Liaoning Province has achieved better emission reduction effects after the implementation of this policy. After the implementation of the policy, the economic development of Hubei Province has been improved, but it has not brought help to the economic development of Liaoning Province. These findings provide new insights into the use of an emissions trading system for improving economic development and ultimately facilitate the attainment of the broader goal of sustainability.

This paper proposes an innovative policy effect evaluation method by considering the status of unit gross domestic product, fixed asset investment in the energy industry, energy consumption, emission reduction technology innovation and other evaluation indicators. This paper contributes to broadening current methods of policy effect evaluation in China.

This paper applied grey wave forecasting in a decomposition–ensemble forecasting method for modelling the complex and non-linear features in time series data. This application aims to test the advantages of grey wave forecasting method in predicting time series with periodic fluctuations.

The decomposition–ensemble method combines empirical mode decomposition (EMD), component reconstruction technology and grey wave forecasting. More specifically, EMD is used to decompose time series data into different intrinsic mode function (IMF) components in the first step. Permutation entropy and the average of each IMF are checked for component reconstruction. Then the grey wave forecasting model or ARMA is used to predict each IMF according to the characters of each IMF.

In the empirical analysis, the China container freight index (CCFI) is applied in checking prediction performance. Using two different time periods, the results show that the proposed method performs better than random walk and ARMA in multi-step-ahead prediction.

The decomposition–ensemble method based on EMD and grey wave forecasting model expands the application area of the grey system theory and graphic forecasting method. Grey wave forecasting performs better for data set with periodic fluctuations. Forecasting CCFI assists practitioners in the shipping industry in decision-making.

This study aims to investigate the effects of graphite-MoS₂ composite solid lubricant on the tribological properties of copper-based bearing materials under dry conditions.

The mixture of Graphite-MoS₂ was inlaid in ZQSn6-6–3 tin bronze and ZQAl9-4 aluminum bronze matrix. These copper-embedded self-lubricating bearing materials were considered in friction pairs with 2Cr13 stainless steel, and their tribological properties were studied by using an MM200 wear test machine.

The results show that the friction coefficients and wear rates of copper-embedded self-lubricating bearing materials are lower than those of the ordinary copper-based bearing materials. The wear performance of the tin bronze inlaid self-lubricating bearing material is better than that of the aluminum bronze inlaid self-lubricating bearing material. The wear mechanism of the tin bronze bearing material is mainly adhesive wear, and that of the aluminum bronze bearing material is mainly grinding wear, oxidation wear and adhesive wear. The copper-embedded self-lubricating bearing materials had no obvious abrasion, whereas the aluminum bronze inlaid self-lubricating bearing material exhibited deep furrows and obvious abrasion under high loads.

These results are helpful for the application of copper-embedded self-lubricating bearing materials.

With the development of the modern technology and aerospace industry, the noise pollution is remarkably affecting people’s daily life and has been become a serious issue. Therefore, it is the most important task to develop efficient sound attenuation barriers, especially for the low-frequency audible range. However, low-frequency sound attenuation is usually difficult to achieve for the constraints of the conventional mass-density law of sound transmission. The traditional acoustic materials are reasonably effective at high frequency range. This paper aims to discuss this issue.

Membrane-type local resonant acoustic metamaterial is an ideal low-frequency sound insulation material for its structure is simple and lightweight. In this paper, the finite element method is used to study the low-frequency sound insulation performances of the coupled-membrane type acoustic metamaterial (CMAM). It consists of two identical tensioned circular membranes with fixed boundary. The upper membrane is decorated by a rigid platelet attached to the center. The sublayer membrane is attached with two weights, a central rigid platelet and a concentric ring with inner radius e. The influences of the distribution and number of the attached mass, also asymmetric structure on the acoustic attenuation characteristics of the CMAM, are discussed.

In this paper, the acoustic performance of asymmetric coupled-membrane metamaterial structure is discussed. The influences of mass number, the symmetric and asymmetry structure on the sound insulation performance are analyzed. It is shown that increasing the number of mass attached on membrane, structure exhibits low-frequency and multi-frequency acoustic insulation phenomenon. Compared with the symmetrical structure, asymmetric structure shows the characteristics of lightweight and multi-frequency sound insulation, and the sound insulation performance can be tuned by adjusting the distribution mode and location of mass blocks.

Membrane-type local resonant acoustic metamaterial is an ideal low-frequency sound insulation material for its structure is simple and lightweight. How to effectively broaden the acoustic attenuation band at low frequency is still a problem. But most of researchers focus on symmetric structures. In this study, the asymmetric coupled-membrane acoustic metamaterial structure is examined. It is demonstrated that the asymmetric structure has better sound insulation performances than symmetric structure.

This paper aims to develop a theoretical method to analyze the rotation accuracy of rotating machinery with multi-support structures. The method effectively considers the geometric errors and assembly deformation of parts.

A method composed of matrix and FEA methods is proposed to do the analysis. The deviation propagation analysis results and external loads are set as boundary conditions of the model which is built with Timoshenko beam elements to calculate the spatial pose of the rotor. The calculation is performed repeatedly as the rotation angle increased to get the rotation trajectories of concerned nodes, and further evaluation is done to get the rotation accuracy. Additionally, to get more reliable results, the bearing motion errors and stiffness are analyzed by a static model considering manufacturing errors of parts.

The feasibility of the proposed method is verified through a case study of a high-precision spindle. The method reasonably predicts the rotation accuracy of the spindle.

For rotating machinery with multi-support structures, the paper proposes a modeling method to predict the rotation accuracy, simultaneously considering geometric errors and assembly deformation of parts. This would improve the accuracy of tolerance analysis.

The information used for supervision by regulatory departments in public-private partnership (PPP) projects is primarily transmitted and processed by the PPP implementation department, which negatively impacts the information quality, leading to information asymmetry and undermining the overall effectiveness of supervision. This study aims to explore how to use blockchain to anchor the information used for supervision in PPP projects to the original information, to strengthen the oversight.

This paper adopts the principles of design science research (DSR) to design a conceptual framework that systematically organizes information along the information dissemination chain, ensuring the reliable anchoring of original information. Two-stage interviews involving experts from academia and industry are conducted, serving as formative and summative evaluations to guide the design.

The framework establishes a weak-centralized information organizing mode, including the design of governance community and on-chain and off-chain governance mechanisms. Feedback from experts is collected via interviews and the designed framework is thought to improve information used for supervision. Constructive suggestions are also collected and analyzed for further development.

This paper provides a novel example exploring the inspirations blockchain can bring to project governance, like exercising caution regarding the disorderly expansion of public sector authority in addressing information disadvantages and how to leverage blockchain to achieve this. Technical details conveyed by the framework deepen understanding of how blockchain benefits and the challenges faced in successful implementation for practitioners and policymakers. The targeted evaluation serves as rigorous validation, guiding experts to provide reliable feedback and richer insights by offering them a more cognitively convenient scenario.

The purpose of this study is to provide effective and environmental-friendly corrosion inhibitors derived from graphene oxide for Q235 steel.

Nontoxic and environment-friendly 4-aminobenzoic acid was used to functionalize graphene oxide via amidation and diazotization. The obtained amidation 4-aminobenzoic acid functionalized graphene oxide (PAGO) and diazotization 4-aminobenzoic acid functionalized graphene oxide (PDGO) were characterized by FTIR, Raman and TEM, while the inhibition efficiencies were analyzed by electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization (PDP). Furthermore, theoretical inhibition efficiencies were investigated by density functional theory (DFT) approach.

At a concentration of 40 ppm, the maximum inhibition efficiency of PAGO and PDGO were 97.90% and 96.72% in EIS measurement, respectively, which were in accordance with PDP data. Moreover, experimental results were supported by DFT-based quantum chemical calculation.

Environmental-friendly PAGO and PDGO were synthesized successfully. The synthetic inhibitors exhibited excellent inhibition efficiencies in EIS and PDP measurements. Furthermore, a computational study using DFT supported the trend that PAGO was better inhibitor than PDGO.

This paper aims to investigate the relationship linking hard technology innovation with the high-quality development (HDP) of SRDI firms. SRDI firms are typically classified as medium-sized to moderately scaled businesses renowned for their specialized, refinement, differentiation and innovation (SRDI), with a focus on providing exceptional products or services to gain a competitive advantage in specific market segments. These firms are dedicated to expanding market share and enhancing innovation capacities both locally and globally. The research also aims to scrutinize the contextual effects of digital transformation within this framework.

Hard technology innovation consists of three essential components: innovative characteristics, newly developed technology-based intellectual property rights and the volume of R&D initiatives. The evaluation of HDP was performed utilizing the entropy method, with a specific emphasis on assessing value creation and value management capabilities. Subsequently, this study explores the impact of technological innovation on the HDP of firms using a dual-dimension fixed effects model.

Every aspect of hard technology innovation is essential for promoting the HDP of businesses. The digital transformation of businesses exerts a heterogeneous moderating influence in this process. This is evident in the constructive impact on the connection between innovation attributes and the volume of fruitful R&D initiatives, as well as the HDP of firms. Conversely, the moderating effect is deemed insignificant in the association between new technology-based intellectual property and HDP.

This research delves deeper into the underlying mechanisms that underlie the promotion of HDP through hard technology innovation, thereby expanding the scope of our exploration on the HDP of SRDI firms. It establishes a theoretical framework and practical directives for achieving enhanced development quality amidst the evolving landscape of digital transformation within firms.

Automatic interpretation of Nominal Compounds is a crucial issue for many applications, for example, sentence understanding, machine translation, question-answering system and so forth. Many automatic interpretation models of Nominal Compounds use the strategies based on verbs or rules to obtain the interpretation of compounds. However, the performances of these models are still limited. The purpose of this paper is to propose an effective approach for automatic interpretation of Chinese nominal compounds.

The authors propose a top-down and bottom-up model based on rules and large-scale corpus for automatic interpretation of Nominal Compounds.

Experimental results demonstrate that the proposed model outperforms the state-of-the-art automatic interpretation model.

The paper is an up-to-date study of automatic interpretation for Nominal Compounds. It can help people understand the meaning of Nominal Compounds in reading. With a better understanding of Nominal Compounds, we can discover more hidden knowledge in them.